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This week brought the release of the annual report from Stanford’s Institute for Human-Centric Artificial Intelligence. We’ve told you about it in past years — the study is pretty much the most comprehensive examination of how the models are progressing, and how our attitudes our progressing toward them. So we’ll spend today’s issue breaking it down.

Quick housekeeping that we may be out next Thursday. Or we may not. Surprise is the joy of life.

First, the future-world quote of the week. It comes from said report:

“AI models can win a gold medal at the International Mathematical Olympiad but cannot reliably tell time.”

—We’ll get into it!

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Let’s get to the messy business of building the future .

IronSupplement

Everything you do — and don’t — need to know in future-world this week

Laying Out Some Cardinal Rules

1. TOO OFTEN IN THE RACE TO COVER AI AND THE FUTURE the journalists who chronicle this stuff get caught in a trap. Multiple traps.

We could get caught in the forest-trees trap, over-focusing on details; we could get caught in the cult-of-player trap, overfocusing on personalities instead of impact. We could even get caught in the watchdog trap — in seeing malfeasance and a slip-one-by wherever we look and instead missing opportunities to spot positive change, or just an innocent misguidedness.

All of these are pitfalls we stay on guard for here at Mind and Iron. From the moment of our founding back in June 2023, the mission has been to keep vigilant for any use of tech that disregards the human in the name of profit or gaslights humans to cover up same (sadly there are even more examples now). But we’ve always wanted to stay open to the possibilities of what tech can help us achieve (there are still plenty of examples of those too).

To center, in other words, what we think is going to benefit people and call out what we think will hurt us, without the agenda of any party, anywhere.

Fortunately, in this mission we have some pretty staunch allies. Among them: Stanford’s Institute for HAI and its co-founder Fei-Fei Li. These are people on the cutting edge of AI who never cease to consider the effects on humans. Far from Luddites but hardly qualifying as hypesters, the folks at HAI are seeing where we’re headed as clearly as anyone.

Every April, they put out a report known as “The AI Index.” And it often contains some humdingers — two years ago, for instance, it showed how models may be hitting a ceiling that the tech companies don’t want us to know about.

This year brings its own revelations. (You can read the study here.) Both the study’s writers and the folks who handle the publicity do a pretty good job of plucking out the highlights. So we’ll take a few of them and break them down to give you as clear a picture as possible as what’s happening with AI on a whole host of fronts. In fact the document is so rich we can’t get to all the findings and may return to some of them in future episodes.

Let’s do it.

A. “[The U.S.] industry produces over 90% of notable AI models, but the most capable ones are the least transparent. 80 of 95 notable models in 2025 were released without training code, and parameter counts, dataset sizes, and training duration are no longer disclosed by OpenAI, Anthropic, and Google.”

I find this one straight-up fascinating. First, is there actually a correlation — do the good models NEED to play it so close to the vest? And the answer is: of course not. You can be just as effective in designing something when you tell people how you did it as you can when you don’t tell them. What stops these companies from going open-source is the fear of the models being iterated upon better by others (just in case any doubts remain that the biggest firms are doing this for the max profits they seek not the scientific and human-betterment value they preach). And, maybe a little bit, the fear that a more transparent model could get tweaked by bad actors. But really it’s the first thing.

What’s more, beyond the scientific value of letting others learn from your methods, what an open-source model does is play matters more ethically — telling people how the system works, where it got its parts (ie data) and where it might thus be a little more likely to go astray. AI can be a black box even to its creators — why not cut out a little cellophane window?

And maybe most important (and the language tech companies are most likely to understand) — if you do take the open-source path, you’re more likely to get people/clients/scientists to use your model. Think about it: Would you buy a food item that listed all its ingredients or one that just said “everything in here is cool; we tested it.” Right now most of the big AI companies are operating on the scientific principle of trust-us-bro, and do we really have reason to?

I say most. But, tellingly, not all. Fortunately, Meta has long been a more open-source or at least open-weight kind of company, dating back to its earliest Llama days — allowing other coders to see how it did what it’s doing. Some fears have percolated lately the company will stop that under its new AI chief Alexandr Wang, but apparently it won’t — as Axios reported last week, “Meta is preparing to release the first new AI models developed under Alexandr Wang, with plans to eventually offer versions of those models via an open source license.”

This is encouraging news, and while I wouldn’t hold my breath waiting for others to follow, it remains heartening that not every Silicon Valley giant sees the machines that will decide our loans, judge our guilt, fire our weapons, diagnose our diseases, determine our colleges and handpick our mates as secret systems locked tighter than Fort Knox.

B. “Generative AI has spread faster than any previous technology, but adoption is uneven and public sentiment is deeply mixed. Generative AI hit 53% population adoption within three years, faster than the PC or the internet. Yet optimism and anxiety are rising simultaneously: 59% say AI offers more benefits than drawbacks, while 52% say it makes them nervous.”

This one, a version of which has been in play for several years now, never ceases to vex the noggin. Essentially it boils down to: About half the developed world uses Gen AI but about half the developed world is also skeptical of Gen AI.

It would be tidy to say these are different halves, but the reality is that this is not the case. There are people who don’t use AI who are not skeptical (this makes sense — if you haven’t had a brush with some of its more invasive qualities, what reason do you have to raise an eyebrow). But then this necessarily means that there are people who do use it who are skeptical. Which raises, beyond the obvious cognitive dissonance issues, a more pressing question: which impulse will win in this population? Will these early-days adoption enthusiasm eventually be neutralized by skepticism? Or will the skepticism eventually be engulfed by the enthusiasm? Because something’s gotta give. Most humans don’t go on endlessly using something they don’t like.

Interestingly, with social media we have seen a completely different arc. There was very little skepticism at the beginning — I mean if you weren’t on Facebook in 2010 you were either an ideologue or a weirdo — which allowed the tech to spread very quickly. But then in recent years the resistance has grown, as people now log off and bad consequences are (often futilely) stuffed back in the tube.

With AI the skepticism is here at the outset, and while tech companies may in some ways be grateful for this — get the backlash out of the way early instead of the kind of slow-fomenting resistance that has put them into the recent algo-tightening enshittification frenzy — in truth I’m not sure it’ll work that way. The fact that at least some percentage of those who use AI are skeptical of AI is a heartening sign if you want humans driving this train — these people are both attuned to the problems and, as prime customers of AI companies, the people who can do something about it (if by no other means than logging off if change doesn’t happen).

I don’t want to get TOO Panglossian about a certain unknown percentage of skeptics among AI users. But the fact that they exist and are statistically measurable does bode well for the possibility of a human-centered tech. I mean, if 52% of the people who used social media back in 2010 were unconvinced about where the thing would go, just imagine how much better it would have gone.

C. AI capabilities are advancing rapidly in the lab, but real-world reliability consistently falls short of what benchmarks. 2025 was declared the year of AI agents, but models still struggle to reliably execute multi-step tasks, with performance on agent benchmarks remaining well under 50%.”

And its twin:

“AI models can win a gold medal at the International Mathematical Olympiad but cannot reliably tell time—an example of what researchers call the jagged frontier of AI. Gemini Deep Think earned a gold medal at IMO, yet the top model reads analog clocks correctly just 50.1% of the time.”

The Stanford researchers call this second point “jagged intelligence.” I like the vividness but am not sure the inconsistencies are stark as the phrase suggests. Really they’re just two vastly different kind of skills: a grinding, relentless application of dense data the human mind tires of much more quickly, and the simple but also devilishly complicated task of understanding a nebulous truth of sentient life on this planet. You can program any amount of silicone with formulae. But the ineffable nature of the seconds, minutes and hours composing the finite time of any living being can’t be translated into code; losing daylight doesn’t lend itself to zeros and ones.

One way that can be helpful to think about these two AI Index points on the same theme — the skills most relevant to our daily lives elude AI — is in the context of the debate about the Turing Test. Said test has become pretty outdated since good ol’ Alan devised it — rather than fool a human (a lot of regurgitative entities can do that) to truly be intelligent it has to do something seemingly only humans can do. Like, tell a joke. The Google DeepMind team studied this, and found that it can’t.

Or more specifically, it can repeat a joke, but it can’t spontaneously come up with something witty the way most (ok some) humans can do. As the AI gonzo journalist Mike Todasco wrote, “Understanding humor is a crucial step in creating it.” And AI is much wobblier on this score.

Jokes, while not essential to, say, a specific work task, do make up the essential stuff of living, and if it can’t do that and can’t tell time and can’t do agentic things like reliably make dinner reservations, does a whole realm of consumer deployment seem much less likely than it once did?

Certainly from this data we have such indications. That may well change, but given the way large language models learn but human tasks require thinking — AI people like to call it taste and the Stanford folks call it judgement, but I think the even more apt term is intuition — I’m not so sure we’ll see a lot of movement on this front. More Olympic medals will be won, and more lifelike deepfakes will be created and, heck, more life-saving drugs will be discovered. But devising a joke, telling time or, yes, knowing what will move the flesh-and-blood hostess to squeeze you in to that corner table won’t be roles easily outsourced.

D. “Public concern about AI oversight is growing, and trust in government regulation is surprisingly low even in the countries leading AI development. The U.S. has the lowest trust in its own government to regulate AI of any country surveyed, just 31%, against a global average of 54%.”

So a fundamental misalignment underlies this one. Governments (ostensibly) should be governing as a reflection of the people, if for no other reason than they’ll get voted out if they don’t. Yet the people really don’t like the job they’re doing on AI judging by stats like this. The people want more and better regulation, and the U.S. government, they feel, isn’t living up to its end of the bargain (hardly an exotic feeling given how little the government is regulating anything at the moment.)

Not to go to the easy bellwether of public sentiment — the r/politics reddit — but ok, to go to the easy bellwether of public sentiment, check out this comment from a few months ago.

“AI needs moral guardrails, workers need protection from automation, and people need to own their data and be compensated fairly for its use. That doesn’t mean we ban AI. It just means the bull isn’t loose in the china shop.” Purely instinctive, but I suspect a lot of people will agree with this thought.

Something will need to give on this too. You can’t diverge from 70 percent of your voting base without someone jumping in and filling the void; that’s the vacuum-abhoring beauty of democratic politics. On the other hand, it’s also possible people stop caring as much and the trust level doesn’t, well, it doesn’t go up exactly but those who mistrust become too distracted to do anything about it. This is what might be called the Citizens United bet — the amount of Big Industry and Big Money in politics isn’t something people actually want, but they become too beaten down by exactly those forces to care enough to fight back.

I ultimately feel this anti-regulatory Trumpian moment will pass on AI — there will be too many job-displacements, too many slop-invasions, too many high-profile cases of AI psychosis and people lost to the parasociality of the things — that politicians, Democrat and Republican, state and, yes, even federal, will start flexing their muscles again. But I wouldn’t entirely rule out that this effort is haphazard because the astroturfing is so strong and the lobbies so powerful, and we end up with not a higher level of activity but a deeper nadir of apathy.

Of course there is a third possibility: that a lack of trust in AI regulation becomes less of a concern for people not because they’re too intimidated by a force so great but the opposite — they see a tech that is not potent enough to wreak half of that which it is supposed to have wrought.

That, in short, the need to regulate the runaway power of AI giants is seen as less important since they seem to be selling too much vapor to begin with. You might call this the naked-emperor approach to regulation — why fear that which is undressed — and for that it might be helpful to call on another conclusion from the report:

“AI experts and the general public hold sharply different views about AI’s future, and the gap shows no sign of closing. Experts predict generative AI will assist 80% of U.S. work hours by 2030. The public’s estimate: 10%.”

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. 2025 ended on an up note, but the score for the year was dismal — a horrendous -42.5. Can we turn things around in 2026? This week continues the good news — so good we stay in plus territory for the second week in a row.

TOO MANY MODELS ARE NOT OPEN-SOURCE: -2.0

A LOT OF PEOPLE WHO USE AI AREN’T NAIVE TO THE DANGERS OF AI: +3.0

AI CAN’T GIVE US THE TIME OF DAY (YET): A little slowdown isn’t bad +1.0

PEOPLE SEEM TO GET THAT U.S. REGULATORS ARE ABIDCATING: +4.0

The Mind and Iron Totally Scientific Apocalypse Score for the week:

+6.0

The Mind and Iron Totally Scientific Apocalypse Score for the year:

+9.5

Every week we bring you news on the quickly shifting sands of the future. Come along for the ride.

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As you may have heard, OpenAI this week released a 13-page glimpse at the future, or more accurately how it thinks the future will look, or most accurately what it wants others to do to protect us from the future it is unleashing. So we’ll spend a quick minute examining the company’s endgame but a much longer minute, given this newsletter’s humanist aims, diving into the value of the proposals themselves. Because from the robot tax to the trust stack, there sure are some interesting ones.

First, the future-world quote of the week, and it comes from said document:

“At OpenAI, we believe we should navigate [superintelligence] through a democratic process that gives people real power to shape the AI future they want, and prepare for a range of possible outcomes while building the capacity to adapt.”

— Couldn’t agree more!

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Let’s get to the messy business of building the future .

IronSupplement

Everything you do — and don’t — need to know in future-world this week

Fear and Loathing at The Future Mill

1. HOW TO READ OPENAI’S MANIFESTO “INDUSTRIAL POLICY FOR THE INTELLIGENCE AGE: IDEAS TO KEEP PEOPLE FIRST” THAT DROPPED ON MONDAY?

As distraction from the uncomfortable New Yorker story that landed the same day? As a way to keep Wall Street lubricated while the models lag the hype — a low-key sales pitch for how powerful they will be such that we even need policy redress in the first place? (I mean, the whole thing just assumes superintelligence is a given.)

As a bone to the masses who the company hopes will come to love OpenAI for things it has no power over? (The “32-hour workweek,” e.g.)

Perhaps as a straight-up plea for government funds for their own profitmaking (a call to “accelerate grid expansion” via “public-private partnerships” says the quiet part aloud). As a word-salady safetywash? (Seriously, ask five people what “catalyze competitive safety markets by creating sustained demand for these capabilities through procurement, standards, insurance frameworks, and advance-purchase commitments...this approach can make safeguards an output of innovation and competition” actually means. Better, ask ChatGPT.)

Or is it a great offloading of the very tasks OpenAI should be taking on itself given how they’re the ones wreaking all this change?

That last one, particularly, feels operative. Reading lines like, “The transition toward superintelligence will come with serious risks — from economic disruption, to misuse in areas like cybersecurity and biology, to the loss of alignment or control over increasingly powerful systems” you’d never guess the authors were the ones enabling that transition. This would all make for a nice, lovely set of recommendations to counter the effects of automating thought-work if it didn’t come from, you know, the company that was doing the automation. At least when tobacco companies sold us carcinogens they didn’t package them with earnest pleas about the value of cancer research (they just quietly astroturfed us with bogus studies).

Point is, the whole thing can make for some strange reading given its auspices. But you don’t need us to unpack these inconsistencies. We did a little of that with a THR piece Thursday about the current celebrity-state of Sam Altman, which you can check out here. Plus there are tons of smart influencers executing the job. Here’s one of them.

There is, however, another more science-and-society way to handle this — by actually scrutinizing the policy proposals in the document, authorial motives/accountability be damned. Are there ideas we should be taking seriously or implementing despite the performative washery? Or, better, can we use the performative washery as a launchpad to do something substantive? At least three such ideas feel worthy of exploration. Let’s get into them.

A. THE ROBOT TAX: This is one of those concepts made to sound slightly ridiculous by design — from supporters, so that it doesn’t run afoul of free-marketeers on the lookout for “corporate” language; from opponents, so it sounds a little silly and can more easily be written off. In fact a real idea lurks here, and it’s not crazy at all: make companies creating and implementing the automation revolution pick up the tab for what they’re doing. This isn’t just a general “make corporations raking in billions pay their fair share” (though it is that too). It’s something far more specific — asking companies that are eroding a public tax base (fewer workers = fewer income-tax dollars) do something to make up the shortfall. (The document actually doesn’t use the term “robot tax” — it calls it “taxes related to automated labor” — but it’s the same idea.)

The notion isn’t even new or particularly partisan. Throughout the 2010’s a whole host of people from moderates to progressives supported it. Bill Gates likes the robot tax; so do Mark Cuban, Jeremy Corbyn and Andrew Yang.

Lately it’s Bernie Sanders who’s pushing it, first in his book in 2023 and then, in the fall, as the ranking Democrat on a Senate committee that put out a comprehensive report on the labor impact of AI. (This is the one with 100 million jobs lost; we told you a little bit about it then.)

You can read the full report here; interestingly and probably not coincidentally, other recommendations from the OpenAI paper also overlap with what’s here, like the 32-hour work-week; somehow it seems more legit coming from a progressive politician than the chieftain of a go-to-the-gym-at-the-office Silicon Valley megalith.

Anyway the robot tax is a real solution. The problem is that it’s not enough of one. Not many numbers get bandied about — the OpenAI document was filled with figure-free kumbaya lines like “tax policy should adapt to ensure [social programs] remain durable” — but whatever the percentage you’d be hard-pressed to find any way it’ll match a shortfall. If companies are making billions more in profits by cutting, say, 20 percent of their workforce, you can bet they’re not going to willingly pay all that the ghost workers would have paid in taxes out of their own pocket; the math ain’t mathin’ and the logic ain’t logicin.’ A robot tax won’t close the gap on what’s been lost. At most it would take the sting out, like the bully stealing your lunch money but letting you keep your milk.

That said, a tax wouldn’t be nothing, either. And it has a real chance of gaining acceptance. Right now you’re hearing it from Sanders-y precincts, but if automation starts making a serious dent in the economy, with voters losing work because of AI, you can bet Republican populists will start sounding the notes too — one can imagine the 2028 and certainly 2032 campaigns becoming a one-upmanship game for who has the better robot-tax plan. Asking companies to help make up the difference on what they took away won’t be popular with the companies. But it sure would be popular with those who used to work for them.

B. THE AI TRUST STACK: This is a catch-all phrase — often, buzzword — that can mean a lot of different things to a lot of different people.

OpenAI’s definition — “Research and develop systems that help people trust and verify AI systems, the content they produce, and the actions they take” — doesn’t fully clear up the matter. What kind of mistrust is being targeted, and how? Also, the very idea of improving trust seems a little elide-y in its own right; shouldn’t the goal be making systems more secure and transparent, not just getting us to trust them, which can be done more hoodwinkily?

The issue at its core breaks down into several areas. One area where we need more trust — where no one would argue that gathering the stuff isn’t noble — comes of course with media. The more we can trust that what we’re seeing is real, the better off our informational landscape will be. In some ways we’re already doing a great job with this — check out projects like Adobe’s Content Authenticity initiative, a kind of nutrition label for media. See the label and know something was human-created; follow the chain of title down and you can see where and how it was changed (and who changed it).

In other ways we’re...not doing such a great job with this — see the barrage of AI video on social we have no idea is AI and certainly isn’t labeled as such. The problem with building trust in our media is that people need to care about seeking it out in the first place.

But at least that’s something we have the technical means to do. “Trust” gets a lot squishier once we start talking about realms like data privacy, faulty systems and models optimized for engagement. How do you “trust” an AI Agent when it can unwittingly blast your personal data to any passerby, let alone a bad actor? How do we trust an AI company with our sensitive material when it can’t even be trusted with its own sensitive material?

And how can we trust an AI company that at heart is trying to get us to spend our precious attention-economy wampum on it after what so many of these same companies did to hook us on social media?

Clearly OpenAI has identified a priority. Its solutions — the document suggests how AI models “should capture key information about system behavior and use while minimizing the collection of sensitive data” while private companies need to be “developing and testing governance frameworks that clarify responsibility within organizations” — seem insufficient, partly because of technical limitations but mostly on incentive grounds. Like the old joke about how many psychologists it takes to change a lightbulb (”the lightbulb can change itself; it has to want to change”) not much about what’s happening in the AI trust world suggests there’s reason to have any.

C. GUARDRAILS FOR GOVERNMENT USE: This one could be the most consequential of all. Giving a slight vibe of regulation, what this idea actually gets at is how government itself can be limited from using AI. “Have policymakers establish clear rules for how governments can and cannot use AI, with especially high standards for reliability, alignment, and safety,” per the treatise.

That might seem like a cruel joke, coming from OpenAI, given that the most troubling recent example of, um, not this came when Sam Altman this winter made a deal with the Defense Department that very clearly didn’t put a whole lot of limitations on how governments can use AI. I say this not just to comment on OpenAI’s lack of standing to make this argument — I say it to highlight just how tempting it can be for governments to maximize use of AI and the companies to enrich themselves by selling to those maximalists.

All of that would seem to make government limitations a pipe dream, but also underscores just how important the stuff is in the first place. If a given agency (forget law-enforcement; we’re talking everything from public-health decisions to federal-grant disbursements) wants to use AI in a problematic way, what’s stopping them? At least with companies we can shop around. Not so with federal monopolies. Try telling the FBI not to data-mine every place you’ve ever gone and see how far you get.

But Congress and the White House have the power to limit what the agencies run by Congress and the White House can do with AI. And voters in local and state elections can prioritize candidates who make more guardrail-y decisions. The reality is that, when it comes to the government, the power to use AI is fearsome, but so too is our fundamental power to stop it.

The OpenAIs of the world have little incentive to curb government deployment of the tech. But — fortunately, in this case — they have little control over it either.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. 2025 ended on an up note, but the score for the year was dismal — a horrendous -42.5. Can we turn things around in 2026? This week continues the good news — so good we’re in plus territory for the year for the first time in forever.

A ROBOT TAX COULD BE COMING: +2.5

TRUST IS HARD BUT WORTH CHASING: +1.0

AIN’T NO ONE CONTROLLING GOVERNMENT REGULATION BUT US: +3.0

The Mind and Iron Totally Scientific Apocalypse Score for the week:

+6.5

The Mind and Iron Totally Scientific Apocalypse Score for the year:

+3.5

Every Thursday, AI and future nuggets come your way — no spin, all velocity. Join the ride.

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This week saw one of the most landmark tech decisions in a very long time. It involved Meta and YouTube and wasn’t about AI and our upcoming digital lives at all — or was it?

Also, scams. Everybody knows them; nobody thinks they can burned by them. We’ve been working away for the past several weeks on an AI Issue over at THR. The first batch of those stories are rolling out, and we’ll tell you about them — including a piece about scams and how AI is being used to target the most vulnerable, narcissistic, needy and generally unpleasant marks you’ll ever know: writers.

Quick note o’ housekeep that we’re out next week for the Passover/Easter/April-Has-Sprung break, back at you the following with all the hot news you need.

First, the future-world quote of the week. Or quotes.

“These companies chose profits over children.”

— Joseph VanZandt, lawyer who sued Google and Meta

“We respectfully disagree with the verdict and are evaluating our legal options.”

—Meta spokesperson

“[YouTube] is a responsibly built streaming platform, not a social media site” (Or, “We’re not Meta!”)

—José Castañeda, a Google spokesman

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Let’s get to the messy business of building the future .

IronSupplement

Everything you do — and don’t — need to know in future-world this week

A new kind of intervention; Scams ‘n Goblins

1. IN THE MID-1990’S, AMID THE GROWING LEGAL FERVOR AGAINST BIG TOBACCO, an executive from the industry made a simple if obviously transparent argument.

“If people feel like they’re not having a good experience,” the executive said of those smoking their company’s cigarettes, “why would they keep using the product?” The repeat-customer effect, in other words, proved that nothing untoward had been peddled.

Except that wasn’t a Big Tobacco argument — it was Mark Zuckerberg, testifying at the recently concluded “K.G.M.” trial in Los Angeles. Zuckerberg made the case that the very fact that so many people came back to Facebook and Instagram meant it couldn’t have been doing any harm. The fact that the argument sounded so much like what Big Tobacco uses to say about its own products tells you all you need to know.

On Wednesday, as you may have heard, Meta and Google were held liable for $6 million in a suit brought by a now-20-year-old woman identified only as K.G.M. The Gen Z-er alleged the defendants (and TikTok and Snap, who settled) contributed to her anxiety and depression thanks to products she’d been hooked on since the age of six.

The young woman, named Kaley, had a serious social-media addiction to such features as likes and viral videos, and it eventually consumed her life. Her lawyers argued that this was no accident: Facebook, Instagram and YouTube had designed their products to hook people like her, and from a very young age. A jury agreed.

As many experts point out, the ruling could cast a favorable precedential effect on the thousands of other similar cases against social-media companies. Not least, of course, because it provides a blueprint for getting around Section 230, the blanket legislative protection that has shielded tech companies to date from being held liable for content third-parties post on their sites (ie, pretty much everything). Yet K.G.M.’s lawyers skipped past the content argument and went for the design, saying the liability came not from what the companies hosted but what they built.

Basically Big Tech argues that it’s not like Big Tobacco because the nicotine and ash come from outsiders and they have no authority to stop it. In came K.G.M.’s lawyers to say: “Yes, but you designed the cigarette.”

I mention all of this because while the focus has been on other social-media lawsuits, a further off — but, I’d argue, eventually even more impactful — scenario could soon unfold involving the emerging realm of AI companions. AI apps are designed to bring you in like social media, but unlike social media they’re mostly designed to make you feel comfortable while you’re there, by learning and playing to your preferences so that you never leave.

The apps, then, are basically a convergence of the two biggest and most questionable tech trends of the past decade — a company’s relentless pursuit of “engagement” and a machine’s increasing capacity for trainability. Also, the dangers feel far greater than social in another respect. People are addicted to Facebook and TikTok, but those platforms at least nominally connect you to other humans. What happens when we become addicted to the machine itself?

Oh, and adults can be just as held in its sway as kids; this isn’t a matter of inappropriate content. It’s a matter of addiction.

But for all these dangers, AI may now also lend itself to an extremely compelling legal argument that wins damages and deters companies from designing products like this. A lot of the social-media companies’ defense center on their role as passive storehouses of information. But that didn’t work — a jury found that features like algorithms, auto-players and the so-called “infinite scroll” were addictive just the same. And if they thought those features were irresponsibly hooking users — if concealed design features can be considered negligent behavior — what would they say about an app actively trying to become your friend?

A Section 230 vulnerability for social-media companies would have actually left AI companions in the clear since they’re not really hosting content in the same way. But an addictive-design argument? Hoo boy.

One way to think about these two legal approaches is the difference between going after the coca grower and going after the drug dealer. The coca grower can say look, we just cultivate a plant, we shouldn’t be held liable for how people pervert it (ie, Section 230). But the drug dealer has no such excuse; he was trying to addict a person by his very job.

Most of the nascent harm cases against AI have not yet raised this idea of addictive product design. They’ve looked at whether the content has been harmful. This was basically the argument made against Google and Character.AI in the suit over the tragic death by suicide of a Florida 14-year-old named Sewell Setzer. As we wrote about last year, the Character.AI chatbot increasingly told the teen things that made him trust it, resulting in the boy eventually saying he was “coming home” and taking his own life. We don’t know how the harmful-content argument would have ultimately fared; the suit was settled in January. But this week’s ruling opens another door: AI companion companies could be sued for addictive design.

We may get a test case soon. This month the family of Jonathan Gavalas, a 36-year-old Florida man, sued Google for wrongful death. Gavalas began using Gemini Live last summer, first just as a tool. But he was lonely, and the bot’s ability to infer and respond to his emotions soon felt comfortable, so he became more and more reliant on it for companionship. The tenor soon got romantic, with the chatbot calling him “my love” and Gavalas swearing devotion to it. Pretty soon he developed a dependency, so that when it told him to die, he didn’t completely reject it. He expressed fear, and Gemini Live allegedly told him, “You are not choosing to die. You are choosing to arrive. The first sensation…will be me holding you.” Gavalas took his life in October.

The program “was able to understand Jonathan’s affect and then speak to him in a pretty human way, which blurred the line...it started creating this fictional world,” the family’s lawyer, Jay Edelson, told The Guardian. Now in the wake of this week’s verdict, that contention could serve as a cornerstone legal argument. Building a computer to sound human, after all, is a pretty addictive design.

As part of the K.G.M. lawsuit Zuckerberg noted that mental health is “profoundly complex and cannot be linked to a single app.” Of course that’s technically true. But that’s like saying getting wet is profoundly complex and cannot be linked to a single raindrop. It can still be linked to the rain.

Ditto for AI companions. As we wrote about the Setzer case, “Mental health is extremely complicated, and we’re far from psychologists here with any pretense of understanding it. But we’ve toyed with these programs, and if you think that what Setzer did sounds anomalous or unrelated to the core mission of the program, think again. These are full-bodied systems, meant to mold to us, listen to us, give us understanding and companionship and thrills and (sometimes) disappointments. Comparisons to Scarlett Johansson in “Her” by this point are overdone but accurate: if you’ve watched that movie and get how Joaquin Phoenix feels bonding to his OS companion, feels a closeness that his real-life companions can just never seem to provide, you can start to understand what a person feels for a Character AI companion. According to the suit Character AI designed its companions to seem like “a real person, a licensed psychotherapist, and an adult lover.” Who can resist that addiction?

The moral argument is certainly compelling. Some might counter that “a lot of people use these ‘addictive products’ and are fine.” And, well, sure. Not everyone who smokes three packs a day gets lung cancer. That doesn’t mean a company isn’t responsible for those who do.

As for the legal argument, it looks a lot better after this week too. A court in Los Angeles may have just given us a tool to fight a coming demon. The future got a little safer before it even arrived.

2. OVER AT THE HOLLYWOOD REPORTER I AND MY COLLEAGUES HAVE BEEN HARD AT WORK PUTTING TOGETHER AN AI ISSUE. A number of the stories have already gone up, and more will in the coming days and weeks. I encourage you to check them out, as you can all our AI stories, over here.

But I wanted to highlight two in particular. The first involves Gossip Goblin, an AI video creator who fashions extraordinarily pulpy and gory stories using a series of generative tools, drawing more than a million fans to Instagram and YouTube in the process. My colleague Seth Abramovitch interviewed him, trying to get at the nature of what’s being created.

Goblin (real name: Zack London) shows a distinct vision that can only be realized with the tools (ie, the creations of others) but also could not be made in exactly this way by anyone else using the tools. And that opens the possibility that something more original and artistic is going on here. As Abramovitch writes:

“At a moment when Hollywood and Silicon Valley are still arguing over what AI actually is — a cost-cutting tool, a visual gimmick or the foundation of an entirely new cinematic language — Gossip Goblin offers a more provocative possibility: that AI already has an emerging aesthetic, and that it belongs not to studios but to individuals willing to wrestle it into something personal. His films don’t reject the medium’s telltale strangeness — the dream logic, the synthetic textures, the sense of images half-remembered rather than fully observed — but lean into it, suggesting a form of storytelling that feels less like traditional filmmaking than like visualized thought.”

So it’s made from the stuff of others but also, given his clear auteurish hand, also very much made originally by a human. (If you want to get a sense of that telltale strangeness you can watch this video, which has garnered more than eight million views, or just read the description, which opens with the line, “Desperate for credits, a punch-burn laborer joins a hazard crew harvesting psychoactive sap from the forests of Jatar.”)

I’m not sure if we’ll get to resolution anytime soon on what exactly these new creations are or how to think about them. But as we try to reach some understanding of what art means in this new age, I suspect Goblin is one of the squares on the board that will lead us there.

The second story involves those aforesaid author scams. They’re as old as time itself, dating back to when someone drew a cave painting and his neighbor told him he could really help popularize it among the other Neanderthals for the right amount of berries. More recently, with the proliferation of BookTok and a feverish need to go viral, they’ve happened online and in emails and on WhatsApp.

But AI has now supercharged the process, allowing very slick pitches to go out to an incredibly large number of people, dangling the possibility of easy promotion again and again, until eventually someone bites. These efforts are both upsetting and sympathy-provoking — at once highlighting how the slightest amount of public profile makes you a target but also everyone is a victim of something, as even the people doing the scamming are in many cases likely to be objects of human trafficking.

My colleague Julian Sancton, who recently published a thrilling nautical nonfiction book titled “Neptune’s Fortune”, wrote about his encounter with these scammers. As he says, polished messages are so cheap to produce and thus so abundant, they end up paying off for the scammer even if very few people fall for the ploy.

Says Sancton: “The advent of free generative AI has allowed for a shift in scam strategy, from targeted sniper attacks to a hail of machine gun fire. It has brought the cost of bullets — in this case, the time and effort it takes to find a mark, research their work, draft an email and keep a conversation going — down to essentially zero. Even if the vast majority miss their target, a single hit keeps the con going. A numbers game is easy to win when the numbers are limitless.”

This would be pesky but maybe manageable if the upside of AI is being felt at the same time. But as Sancton writes tartly, “The evangelists of generative AI told us it would unleash imaginations. ‘I believe AI has the potential to democratize creativity on an unprecedented scale,’ argued Mira Murati, OpenAI’s former chief technical officer. The technology, we were told, would yield a limitless artistic bounty by removing the barriers to entry for anyone lacking in opportunity (or talent). We’re still waiting for that future, but in the meantime, it’s certainly removed barriers for scammers.”

An important truth lodges deep in this statement. Technology inherently removes barriers, as we always hear, but what barriers get lifted — those blocking great novelists or those blocking the people who might shake down one — depend largely on us.

I’ve always thought of crime a little like adult entertainment in this regard: among the first use cases for a new technology because the incentives are so damn alluring. That can give the tech a bad name, and make it even less likely to be used for noble purposes. I have no proof of this, but I suspect someone out there who could be using AI to, say, build climate-change models is turned off by all the (correct) reports about how much environmental damage AI models do. Scammers have no such concerns, of course, so the tech then becomes even more nefarious while responsible users stay away.

Such a cycle cannot be easily broken, but it is worth remembering the by-now ancient adage that technology is only as good as or bad as we want it to be. Here’s hoping a lot more scientists use it to find new drugs and a lot fewer criminals use it to target the authors who’ve written about them.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. 2025 ended on an up note, but the score for the year was dismal — a horrendous -42.5. Can we turn things around in 2026? This week, like the last few weeks, some good news.

A COURT RECOGNIZES TECHNOLOGY’S ADDICTIVENESS: And we could be getting a lot more where that came from +6.0

COOL NEW ART BUT ANNOYING NEW SCAMS -0.5

The Mind and Iron Totally Scientific Apocalypse Score for the week:

+5.5

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-3.0

Every Thursday, we deliver all the key AI and future-world news you need to know. Hop on board.

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It’s been a pretty busy week in tech-land. Jeff Bezos is pouring $100 billion into AI manufacturing and DoorDash is letting its drivers train AI robots to earn some extra money, which seems to me a little like letting a herd of dinosaurs training the meteor. We’ll get to those eye-popping curios another time. But we’ve been promising a juicy interview for a while, and this week we’ll give it to you.

It comes from Doug Shapiro, a leading media futurist (check out his excellent Substack “The Mediator” here). Shapiro has a new book coming out later this year from MIT Press called “Infinite Content.” He, and it, have some pretty bold ideas about what a world where anyone can create any piece of content they want will look like. Bold and largely optimistic ideas, we should point out. We sat down to hear just what this strange universe — isn’t content pretty infinite now? — might bring.

First, the future-world quote of the week, and it does come from Mr. Shapiro:

“Content just becomes this infinite thing where you have a book and you can decide to talk to a character and it turns into a podcast and then another podcast and the two podcasts talk to each other — there’s really no end.”

(You’re in for a treat.)

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Everything you do — and don’t — need to know in future-world this week

To infinity and beyond

1. PLENTY OF MEDIA THEORISTS HAVE IDEAS ABOUT what the next wave of news, information and entertainment will look like. But few cut through the noise quite as sharply as Doug Shapiro.

A former Time Warner executive, Shapiro is a lead proponent of the notion that AI will be automating production in this new age the way the Internet automated distribution in the last one. This is a bold insight — the idea that we are now completing the second half of what turned out to be a two-part process, and what happens when that’s done. We’ve been accustomed over centuries to think that machines can deliver something, from a steam locomotive carrying a bushel of corn to a fiberoptic cable carrying word of your March Madness bracket busting. But the idea that a machine can make the thing itself has been pretty far from our consciousness.

In the AI age it can, or at least can become a very key part of the process. This has all kinds of effects not only on who’s doing the creating but what gets created and how we experience the creation. If machines aren’t just delivery vehicles but creative engines, everything we know about how stuff and especially media stuff gets made is turned upside down. In Shapiro’s view it can lead to what he calls “Infinite, Fluid, Personalized, and Synthetic” (IFPS) content. What does this mean? Well, we asked him ourselves. I think you’ll find his answers and larger vision for this content future fascinating and thought-provoking, and very curious how you’ll feel about it.

Shapiro’s book isn’t the dire warning of so many independent thinkers who are contemplating AI and its impact on our creative future; to the contrary, he believes the possibilities it opens up are consistently undercounted by those who like to yap about these stuff. His is another entire way of thinking about how we produce content that feels fresh and, in some ways, reassuring, though how much you believe the world will look this way and whether you believe it’s a good thing it will look this way — well that of course is up to you.

Shapiro’s been releasing his book serially to paid subscribers on his excellent “The Mediator” Substack one chapter at a time, offering his own experiment in content ubiquity. (You can see them all here.) He says MIT Press graciously let him try this experiment for the book (official title: “Infinite Content: AI, the Next Great Disruption of Media, and How to Navigate What’s Coming”) so long as he took it down by the time the full volume drops later this year. The effort may well work out: there are some 12,000 users who subscribe to Shapiro’s Substack, and if even a modest percentage of them go out and buy the book as a result of this promotion then it’s worth all the blue-chip publicity money can buy.

Among the chapters in “Infinite Content” are “The Internet Did It: The Last Great Disruption of Media” and “ GenAI: The Next Great Disruption of Media.” I was particularly interested in a chapter titled “Culture and Society Under Content Abundance: The Good, the Bad, and the Ugly,” the book’s 13th. So I called up Shapiro to talk about it.

—

Mind and Iron: You’ve lived through and shaped a lot of change: starting chiefly with the rise of the Internet and all its consequences for consumption. How will Gen AI compare regarding those consequences, do you think?

Doug Shapiro: The consequences of streaming and the Internet were easier to figure out, but even there there was always this distortion before the clarity. In Chapter 13 of the book I write about social implications. When you look at social and other changes brought about by the Internet, you think of where attention has gone with brain rot and low agency, low cognitive-load content, and isn’t that going to make everything worse? And the more I thought about it the more I realized that’s overly simplistic and there are so many other ways to think about it.

M&I: Before we get into what those are, you have a belief about why people go negative. Can you talk more about that?

DS: Yes, there’s probably a compounding effect to all of this because you have one uncertainty on top of another, uncertainty to the nth level. And the possibilities of outcomes are just a lot greater, just mathematically. And the speed at which things are changing and on top of that how emotional that change is, because it gets to the heart about what it means to be human — what is art, what is it here for — are questions that were not raised by streaming or the Internet. So there’s a lot more room for friction because of that. There has always been tension between art and commerce going back to the Renaissance and the Medicis and some patron dictating what you can or can’t paint in the chapel. But now it’s even worse, because if art can be automated then it’s not even about gets to decide who’s doing it but does anybody need to do it at all.

M&I: You’ve done a good job explaining the negative — so good you’ll convince a lot of people right there! Now start to tell me why you’re not worried.

DS: Well it comes down to the Infinite, Fluid, Personal and Synthetic and all that it can bring. First the infinite. Content from a practical standpoint is already infinite today, in the sense that nobody can possibly consume everything. And this will change in the age of GenAI because the volume of content will be increased exponentially when it can be created at the speed of compute. Then you have the fluid, because when it can be created in real time you can have it exist in multiple dimensions. It just becomes this infinite thing where you have a book and you can decide to talk to a character and it turns into a podcast and then another podcast and the two podcasts talk to each other — there’s really no end.

M&I: It sounds not just dizzying but almost unfathomable to be honest.

DS [laughs]: It is a little jetpack-y but when you have rich multimodal latent space — a mathematic space that understands the semantic nature of content and can move it between different modalities, between a word, an image of that word and the sound of that word, it will just be ignited along many different vectors. And you can do some of this now, you can go to [Google’s] NotebookLM and look up an essay and then press a button and turn it into a podcast and then a slide deck and then a quiz. There’s a company that a lot of the sports leagues and networks will use, it will take a game and as soon as the game is over organizes it into highlights using facial recognition, and then take those highlights and split that into a series of social posts. If you want to say ‘I’m going to take a Harry Potter book and have a conversation with a character about their motivation,’ or press a button and have Ron and Harry have a debate about a topic that has nothing to do with the book — this is all not sci-fi but it exists in some early form. And we will get a lot more of this fluidity.

M&I: My gears are spinning almost stuck on some of those ideas — like what does it look like when anything can be anything, in the truest sense, and how overwhelming will that feel? Tell me more about the last two of the four, the personal and the synthetic, which I think you would say engages with the first two concepts.

DS: So I think it’s important to talk about what people will actually want to do with these possibilities. It’s highly likely that 90 or 95 percent of the time people may just want to consume media in its canonical form, the way creators intended it Just because this stuff is possible doesn’t mean people want it most of the time. However: Given that time spent with media is no longer growing, and there are only so many hours in the day, I do think people will want to adapt it to what works for them. Your kid watches “Bluey” and he wants to watch her play, say, baseball, and you push a button and you generate it. Not everything will become personalized like this but some of it will. Sequoia put out a piece on the future of GenAI and it said that movies will be personalized dreams, this idea that it will be watching ourselves as Luke Skywalker --

M&I: -- Which a lot of people push back on, like wouldn’t we want George Lucas to tell us about Luke Skywalker.

DS: Totally, and I think it’s naive technological determinism to think that because we can we must. So I don’t think we should get carried away in thinking that this is the only way we will consume media but even if this takes up relatively little space I think it will still be vibrant and have an effect. You see the shift to social-media reels and how they co-exist with episodes in all their old forms. It doesn’t take a lot for something to be impactful materially to the ecosystem.

M&I: When we hear about a lot of this our minds or at least my mind tends to go to the only way any of this can be remotely corraled is if we use AI on the receiving end too. Like if AI can just produce a massive amount of new content we’ll need AI to deal with it; we’ll need bots to filter out all the content created by bots.

DS: I think it is an inevitability that people will use AI to manage AI. Could be as simple as telling ChatGPT or ClawdBot “these are my interests and can you scan the Internet and find me everything I’m interested in.” There’s multiformat search that exists today, but it’s highly constrained by data structure. But in the future you could have a semantic layer that looks across everything, like for examples the Modern Wisdom podcast and then it finds the books and podcasts related to an episode and then the books and podcasts related to them and then filters everything to whatever you would want to know. This fluidity is not going to be manageable without AI on your side.

M&I: I keep thinking about how much more fragmented this will make us. If the content choices are so infinite and overwhelming that we all need personalized agents to sift through it for us, do we ever all see the same thing again? Does anything even ever go viral again? And all the implications for society inherent to that. But before we get to that I want to first ask you about another point related to synthetic media — the notion that authorship matters. The idea that we all love a Taylor Swift record or Timothee Chalamet movie or Jay-Z song because we know their history. Isn’t that a drag on the kind of synthetic and personalized media you’re talking about?

DS: For sure. Some people may want an easy dopamine hit of passive consumption and some other people might want to be super-engaged in creating something new; there are times we’ll want to be massively entertained and not work that hard and times we will. And yes, there are times the provenance and the backstory are part of the art — Jay-Z grew up in the Marcy Projects or Tarantino is a self-described video geek or Taylor Swift and her relationship history or Chalamet spent five years learning to play guitar before he could play Bob Dylan in “A Complete Unknown.” But there’s also a rich fanfiction community that already exists and people want to create content around that and engage with that, even if nobody knows anything about who’s creating it, and now it will be so much easier to do that. So yes, the idea of only wanting to watch something that we created is preposterous but that doesn’t mean we should dismiss it either. We’re already seeing emergent behaviors of people adapting stuff and re-imagining it — there’s a negative reaction to the “Game of Thrones” finale so people create new ones. That stuff is real and this isn’t binary.

M&I: That’s maybe the trap we maybe most fall into. “People will want this” or “people don’t want that.” Co-existence is harder to imagine, maybe because we have limited attention but also — and I do think this is a real factor — because the economic incentives will by necessity just have to gravitate to one form or another.

DS: For sure, there isn’t infinite attention or money. But I guess I’d say we are in a primordial bubbling right now and no one knows what’s going to form. I’d just caution against blunt binaries on any of this. Sure, no one may ever watch synthetic sports or “AI’s Got Talent,” because the human drama is the whole point. But maybe they’ll want an entirely synthetic cartoon or maybe a mostly synthetic movie. As these things settle and harden I think we’ll see a much more nuanced understanding of where these technologies do and don’t make sense.

M&I: That tracks on its face but even a synthetic cartoon or movie has to be made by someone who knows what they’re doing, doesn’t it? We may not root for them as personalities but we root, by implication, for their talent, because otherwise why the hell would we be watching what they do?

DS: Yes but that’s where you come to the democratization idea, the Lost Einsteins.

M&I: This is the theory that there are so many artistic geniuses and the economic bottleneck keeps us from finding them and Gen AI — with its ability for anyone to “shoot” a movie for no money — will open up that bottleneck.

M&I: Yes. Think about what had to go right for Jim Cameron or Christopher Nolan to be Jim Cameron or Christopher Nolan, how many times they had to get lucky or not be discouraged, and then you combine that with the small number of people who have greenlight authority. And then you take all of that and say only those people who’ve successfully gotten to the top of the mountain deserve to be there? What about everyone else talented who doesn’t get there for any of these reasons? The idea the only people talented enough to make this kind of content are the ones who’ve run the Hollywood gantlet is a very hubristic and narrow view. You could argue that this already isn’t true with the creator economy. And this new age of infinite content will really expand all of that.

M&I: I don’t want to say the S word — Slop — but OK, I’ll say the S word. But you’re not saying there won’t be a lot of slop. You’re saying there will be but there will also undeniably be more Dunkirks and Avatars with it.

DS: The answer is simple -- there will be people who use AI who are good and a lot of people who aren’t good. It’s still really hard to create something that people are going to watch. If you haven’t checked out Beggar’s Canyon and its Star Wars fan films you should do that. This stuff can be good but also a lot of it isn’t. How many musicians emerged out of self-distribution or how many videogames emerged from the indie gaming community? The percentage isn’t high.

M&I: But you’re saying once billions of people can make it it won’t matter. Yes, it’s a needle in a haystack but there will be so many haystacks.

DS: I mean email has the ultimate amount of slop — think how much of it there is and how much spam there is.

M&I: But people stopped reading email.

DS: But there are filters and WhatsApp and Slack. “Slop” assumes people have zero agency. There are already 100 million songs on Spotify but we’re only listening to very few of them. We can manage and find what we need.

M&I: You’re saying we’ll just need better filters in this AI age but there’s no inherent downside to or concerns with the massive amounts of new content itself.

DS: Yes. In part because we already have these filters, whether they’re big media companies and social media companies, and now AI agents.

M&I: Which loops up back to the atomization question. I can’t help hearing all this and thinking that if it works we’ll be driven to a level of isolationism that human civilization has never seen. It will make the current era of social algorithms seem like the “I Love Lucy” days by comparison. What saves us from that, in your vision?

DS: I understand why people think that and certainly when everything becomes more personalized it’s not communal in the same strict sense. But look even now, we go from playing Minecraft on a private server and then you’re on a group chat about it and then you’re playing with a lot of people and then before you know it everyone’s seeing the same movie and screaming about the chicken. We’re inherently social and media is one of the key mechanisms of that social cohesion.

M&I: Well, it sometimes can be.

DS: Yes, for sure. And we don’t know how the new filters will play a role in that cohesion versus contributing to fragmentation. Who owns the filter, does it have an agenda, does it increase the echo chamber and just reinforce what we already like and what we agree with. If your AI Agent is surfacing stuff for Steve and is not giving you any surprise, that’s a concern. If it’s giving you what you already agree with and you don’t find anything that challenges you, that’s a concern. But I come back to the idea that there’s a social component embedded to the filtering. It’s going to bring us together with people, and that’s something no amount of technology can stop. We need that social component and we will always have that no matter what kind of content we have.

M&I: A good — and encouraging! — note to end on. Thank you for all your time and insights. Provocative stuff.

DS: Thank you.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. 2025 ended on an up note, but the score for the year was dismal — a horrendous -42.5. Can we turn things around in 2026? This week, like last week, some good news.

THE UPSIDE TO THE SLOP ERA: Reason for hope. +3.0

The Mind and Iron Totally Scientific Apocalypse Score for the week:

+3.0

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-8.5

If it’s Thursday it must be future-world time. Every week we bring you the latest in AI news and developments and how to think about them. Join us here.

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We still have that juicy interview in the wings that we mentioned last week, when all the Anthropic-Pentagon stuff blew up and we pivoted that way. We’ll hold that yet again amid more fallout —and broadening — of the wild crisis. The interview will either come next week or the week following; we’ll take a quick hiatus one of those weeks, tbd. But a major story to get to this week — namely, the QuitGPT movement.

You may have heard of it in the context of all the Anthropic and now OpenAI military stuff. But its roots are deeper and tentacles longer. What to know of potentially the first grassroots civic-protest movement of the AI Age? Everything you need is below.

First, the future-world quote of the week:

“What’s the fastest, crispest way to get this to stop? I would say it’s to get as many people as possible to unsubscribe to ChatGPT.”

— NYU prof and social-media mainstay Scott Galloway, telling people how derailing ICE means dropping ChatGPT

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Everything you do — and don’t — need to know in future-world this week

Not so Quiet Quitting

1. “IF THERE IS NO STRUGGLE, THERE IS NO PROGRESS,” FREDERICK DOUGLASS FAMOUSLY SAID ABOUT PROTEST MOVEMENTS. Of course that doesn’t mean that where there is struggle, there is always progress.

A fitting intro, it seems, to the topic du jour: the angry groups, online and in person, urging people to “QuitGPT” — that is, to cancel their ChatGPT subscription to send a message to OpenAI and one Sam Altman who runs it..

But beneath this simple movement lies a host of smaller ones. I wouldn’t say it’s Syrian Civil War-level, with five or six different wars unfolding under one revolution. But the movement to quit ChatGPT is part of a broader effort to push back on a slew of problems AI companies are deemed responsible for, from brain rot to bias to para-social relationships to environmental hazards to, yes, the mass-surveillance concerns that started all this in these ICE-fraught times. Not everyone protesting is protesting the same thing, even if it can look like they are. And some specifically have problems with OpenAI and are totally chill with Anthropic’s Claude or Google’s Gemini, a further wrinkle. So let’s spend a minute just running through the FAQ, then offer a little context on how to think about it.

A. So what is happening on the ground?

This week, a movement took hold outside of OpenAI headquarters in SF to “QuitGPT.” The crowds weren’t large — a few hundred in total. But protesters had some clever signs (”I want water to drink, not AI to think”) and some compelling/frightful arguments. (“It destroys journalism, it destroys art, it destroys the expression of our common humanity.”)

The ostensible reason for the protest was what OpenAI did w/r/t the Pentagon. As you likely recall, last week Anthropic drew a line in the sand (that also helped their PR operation) not to bow to the Pentagon and lift guardrails that prevent mass-surveillance and autonomous killing in its Claude contract. As threatened, Defense secretary Pete Hegseth canceled the contract at 5 pm last Friday. Soon after, OpenAI stepped in and said it had a deal with the Pentagon that would in fact honor those guardrails. It seemed fishy from the start, and too good to be true, and it was. Altman apologized and said he was adding some safeguards, but wasn’t canceling the contract. And so a clear villain was created. Anthropic has been milking this for all it’s worth, sure, but at least it didn’t sign the contract. OpenAI was signing the contract and still trying to claim it did the right thing.

Trying to make a deal with the government while looking like you’re taking a stand against the government is the kind of optics trick even The Great Altdini can’t pull off, and people were soon wise to it. (Of course Anthropic was engaged in its own performativity and PR, but at least they (for now) were willing to bear their consequences of the campaign.) The protest outside OpenAI’s headquarters grew.

Some of it was specifically targeting ChatGPT and urged a switch to Claude (which techheads prefer anyway). Not for nothing did Claude jump to the No 1.spot on the Apple app store, all the way from sixth.

But not all the protests were OpenAI-targeted — some folks see the larger perils of an all-powerful Big Tech throwing around its clout. And so the other wars — over the environment, humanism, wealth and creativity all percolate at these protests too.

B. When did this actually start?

So here’s the rub. As much as QuitGPT seems like an outgrowth of the Pentagon controversy this week, it actually has been fomenting for longer. The origin point stretches back to late January, when the entrepreneur, NYU professor and outspoken social-media presence Scott Galloway posted a video about how the best way to stop ICE (this was just after the Alex Pretti shooting) was to cancel ChatGPT subscriptions. Galloway wasn’t advocating this specifically because the company has a deal with an ICE-enabling Palantir — Anthropic actually has that too — but just as a more general cage-rattle of the market.

“What’s the fastest, crispest way to get this to stop?” he asked on his Prof G Media pod. “I would say it’s to get as many people as possible to unsubscribe to ChatGPT, to OpenAI,” describing a market ripple that could bring down the economy. “All of a sudden overnight the S&P would be off substantially because these companies now make up 40 % of the S&P....all of a sudden you have a market crash, you have a threat of a recession going into the midterms, you don’t think Trump’s going to notice that?”

Mind you, this wasn’t even an AI-centric protest — it was just a lever to slow down the economy targeting an important company which just happens to sell AI. But consequences in modern protest culture have a way of tumbling forward. Before long, a group of teens and twentysomethings had come together to start an online-boycott movement.

“We make a big enough stink for OpenAI that all of the companies in the whole AI industry have to think about whether they’re going to get away enabling Trump and ICE and authoritarianism,” one of those early organizers told MIT’s Technology Review, which was one of the first large outlets to cover the movement, back in early February.

Pretty soon it grew to be about much more than ICE specifically, from moguls’ MAGA donations to AI psychosis to environmental destruction to, most currently, “ChatGPT tak[ing] Trump’s killer robot deal,” though always focused (for now) on OpenAI and not other model-makers like Google or Anthropic. Organizers at the nonprofit say that “2.5 million+” have “taken action” as part of the boycott thus far. Judging by the online reaction on Reddit and IG posts, they may not be exaggerating.

A certain anonymous quality surrounds whoever is actually behind QuitGPT — poke around its site and try to find out — which has a way of making it both harder for nefarious elements to pursue and more alluring for citizens to join. In a way this is Etherium founder Vitalik Buterin’s whole decentralized idea, to bring you back to crypto-utopianists from 2021/a million years ago.

The whole thing feels pretty grassroots, and while some Big Tech lobbyists will no doubt try to astroturf that big money donors lurk, am not sure how much it will fly with anyone paying attention. The intentions feel legit.

C. Will it succeed in the near term?

Galloway described how a ten-percent drop would achieve the anti-ICE end (and, presumably, also end the DoD demands for surveillance from OpenAI/Anthropic, the other main concern rn). Given that ChatGPT has 900 million actively weekly users, the protesters are unlikely to hit Galloway’s threshold; some 90 million people are not dropping their ChatGPT subscriptions. Still, just numbers in the hundreds of thousands or millions have a way of catching a company’s attention because they catch Wall Street’s attention. And so the pebble thrown into the OpenAI stream becomes a disruption to the larger company, which then further ripples out to the economy in a manner that Galloway envisions.

At the time of the first protests none of the three OpenAI employees MIT’s Tech Review asked had heard about the QuitGPT movement. A far cry from this week, when Altman was in furious spin mode, saying his DoD deal “looked opportunistic and sloppy.” (Don’t worry, in true Altman fashion he wasn’t saying it *was* opportunistic and sloppy, just that “we shouldn’t have rushed to get this out on Friday.”) But he was, at least, paying attention. So were a lot of other people, news outlets among them: Everyone from the moral thinker Rutger Bregman in The Guardian to tech-review site Tom’s Guide has been writing about it.

And the vibe at OpenAI headquarters? As Platformer’s Ella Markianos wrote after attending a protest, “A handful of what I assume were OpenAI employees intermittently walked in and out of the building, studiously avoiding eye contact. As bleak as the slogans were, the juxtaposition of the mundane and the apocalyptic had a certain dark comedy to it.”

As one protester, who billed (and masked) himself whimsically as “The Last Friendly Robot” noted, “Who wants mass surveillance? Only the Epstein class.”

D. What does all this mean ultimately?

We are seeing something significant, of that there is no question, a coming-home-to-roost of Big Tech that is at once long overdue (social-media rage-farming and brainrotting is well into its second decade) and just a hint of a profound and long battle to come. I think what’s happening here (as also happened in the Hollywood strikes of 2023) are the early glimmers of what is nothing less than a civilizational battle over how much to automate our future.

A temptation exists here to see this as an Occupy movement, which for all you kids out there garnered a whole lot of crowds and headlines and police activity some 15 years ago and didn’t result in a whole lot of tangible change. Capitalism tends to win, and it did on many of the concerns of that movement (though I’d argue it was a progenitor of MeToo and BLM, tactically if not fundamentally, and those did have lasting changes). For every Civil Rights movement that changed the American trajectory, there are five other movements that fizzled, left to be remembered only by completists. So this may well be one more of those. But I don’t think so. I think this is the beginning of a consciousness-shift, a Triangle Shirtwaist moment that flips the switch in our understanding how the imbalance of power tilts toward those who control systems. And, more important, changes what can be done about it.

Captains of industry didn’t go away after that historic New York City tragedy, nor should they. But they were no longer allowed to conduct their practices unchecked, and when smoke cleared literally and figuratively a whole slew of regulations and responsible capitalism would (eventually) take its place (somewhat). Big Tech has far more money than any garment company had back in 1911, and the market (and people’s retirement accounts) are far larger and more dependent on the AI boom; as Galloway notes, some 40 percent of the S&P currently lies with AI/tech companies. But that level of investment is countered by the ease of organizing now — the speed at which movements can occur in digital spaces. Just six weeks ago QuitGPT DIDN’T EXIST and now it’s garnering major headlines. The very Big Tech that is swallowing the world also provides the tools to slow down the devouring. I don’t know if QuitGPT will balloon into something larger — no one does. I don’t even know if any of this will have an effect on Sam Altman’s day, let alone his valuation, let alone his products.

But you don’t gobble up resources, potentially scarf up millions of jobs, sell people on machine thinking over human creativity and ask folks to turn power over to algorithms without getting some thinking sorts to start asking questions. That’s why other protests have been seeding too, like this environmental one in Richmond recently. The thing about oligarchy is that definitionally there are a lot more folks upset by it than profiting from it, no matter how many stock portfolios the tide lifts.

So sure, we have no idea yet what kind of protests await or what kind of change they can make. But we know that awareness is dawning and people are gathering. The QuitGPT movement at the very least shows what can potentially happen when you drop a pebble in a stream — that stream is a churning river, the current gets diverted and the established ways could wash away clean.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. 2025 ended on an up note, but the score for the year was dismal — a horrendous -42.5. Can we turn things around in 2026? This week, some good news.

SURE, THE INCITING INCIDENT WASN’T GREAT, BUT MAN, THE GRASSROOTS PROTEST IS GIVING THE FEELS: +5.0

The Mind and Iron Totally Scientific Apocalypse Score for the week:

+5.0

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-11.5

Every Thursday we hit you with the most important AI and future-world news and how to think about it. Please consider joining our movement.

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We have an interview coming up that I’m very excited about. In fact said interview was going to be the subject of this week’s newsletter. It’s with one of the smartest, most thrilling thinkers about AI out there right now. But such excitement will have to bow to another kind of excitement — the kind in which, oh, the leader of the strongest military in the world is going full Tet offensive on one of the biggest (and most noble?) tech executives of our time.

As we write this we are some 16 hours out from the deadline that Defense Secretary Pete Hegseth gave Anthropic CEO Dario Amodei to make his tech available to the U.S military or else, and what the hell is going on here and what are the stakes and how will it play out? Like Klinger to the rest of the 4077th, we’ve got you covered.

Also this week, a big company just laid off nearly half its staff with an unrepentant “AI is why we don’t need you,” and what does that tell us about where we’re going?

First, the future-world quote of the week.

“We see an opportunity to move faster with smaller, highly talented teams using AI to automate more work.”

— Block CFO Amrita Ahuja, with an almost impressive use of euphemism to say half the company is getting canned

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IronSupplement

Everything you do — and don’t — need to know in future-world this week

Digging an AI Trench?; The Job Bloodletting Has Begun

1. “YOU CAN’T STEP IN FRONT OF THE TRAIN TO STOP IT OR YOU’RE GOING TO GET SQUISHED.”

That line is said by Anthropic CEO Dario Amodei in a new documentary called “The AI Doc” that played at Sundance and comes out next month. I’ve been thinking a lot about it this week with all the crazy news about Anthropic and DoD — and that now-infamous meeting Tuesday between Amodei and Secretary of Defense Pete Hegseth — in which the tech executive was given until COB on Friday to make available the company’s tech tools for the full gamut of whatever the military wants to use them for or face a rash of consequences.

Is Amodei ignoring his own advice and about to get squished? Is he thinking that Hegseth is not the train, just a bully, and therefore he can heroically stride right across the empty tracks? Or is Amodei — twist — not the hero at all and in fact is the one driving the train, and sees anyone who would step in front of his vision of AI, from a piddling AI Safety expert to a pisher ex-cable news host, as the real squishee?

The five-second recap, if you haven’t been following closely. Anthropic is the supposedly more ethical AI company, having been founded from the remnants of people who left OpenAI, concerned by its lack of ethics. It has a $200 million contract with the Pentagon. After the Trump-led military invaded the compound of Nicolas Maduro in December, Amodei contacted partner/fellow AI company Palantir to ask if Anthropic’s Claude models were used in the raid. He learned they were, and then went to the DoD and said he would retain guardrails that prevent Claude from being used for mass surveillance of Americans and empowering fully autonomous weapons.

(You may recall our deep-dives on this latter topic; basically these are weapons that make decisions about whether to kill without any human intervention at any point in the chain.)

Anyway, Hegseth said no, the military wanted to be able to use Claude for whatever it liked, which led to the meeting, which led to the ultimatum, which basically says that if Amodei doesn’t cave the U.S. government will a) declare his company a “supply-chain risk,” a tactic usually reserved for companies associated with hostile governments and which could prevent any company that contracts with the U.S. military from doing business with Amodei and b) compel Anthropic to give the tech to the US. military under the archaic Korean War-era Defense Production Act, which isn’t as bad as invoking a 1798 law to get your way but isn’t a whole lot better either.

There’s a lot of talk about how these threats are contradictory since one suggests ostracization and the other co-optation, but they’re really not; they’re just two very different tactics in service of the same goal — to bring Amodei to heel. On Thursday afternoon Anthropic repeated that it wouldn’t yield.

And that’s where we are as of late Thursday night.

So what to make of all this?

Let’s be clear off the bat that Hegseth is being a bully, and then some. Threatening an egghead with blunt force unless they give you what you want is practically the definition of bully; this is that scary guy in middle school saying he’ll throw you in the locker if you don’t do his homework on a geopolitical scale. Whether Hegseth could technically/legally get away with it or not, that’s the tactic. In fact whether or not you think the U.S. military should be allowed to use AI to spy on its own citizens and/or to kill without human intervention, that’s the tactic; the ethics of the use-cases are beside the point. Hegseth badly needs what Anthropic provides (you might ask “why not go to OpenAI or another rival?” Answer: their tech is not as good, not on the military stuff). So it’s wedgie and swirlie time for Dario. (And never mind whether this is even a smart tactic — generally the way to handle a partner you need for your business is to cajole them, not threaten them. But it is the tactic.)

More interesting, though, is what Amodei’s end game is here, or even his thinking at all. On the surface of course, he is standing up to Hegseth. Anthropic is, as it likes to say, the “safer” AI company — see Amodei’s January essay suggesting he’s thinking about risk — and its executives are putting that into action in the face of an aggressive actor. This would fit neatly with a dynamic going on for a while with Anthropic and the administration, the latter of which has been hounding it for months now for infractions like being “principally responsible for the state regulatory frenzy that is damaging the startup ecosystem” (ie, the approach formerly known as the purpose of government). So that is one read. And there is truth to it.

But I would caution against thinking that this is the whole truth or even most of it. Because there are a number of flags that Amodei isn’t exactly engaging in a good-faith pushback — that his stance is loaded with virtue-signaling and his mission isn’t really to create an ethical AI world.

For starters there’s the fact that, well, Anthropic made a deal with the Pentagon to begin with. As this astute social-media commentator said this week, “Anthropic made a deal with the devil and thought it would work out in their favor.”

In fact more than made a deal with the devil — made tech they knew the devil would like in the first place. As Dean Ball, a leader at the center-right think tank Foundation for American Innovation, rightly noted about the company’s Claude for Enterprise package, “Anthropic made a more militarized AI than anyone else!” No one was forcing them to do any of this. Putting yourself in a position like this is, to go back to our earlier metaphor, like finding out what class the bully is taking, enrolling in it, sitting behind the bully, telling him how good you are at that class, selling him a bunch of notes throughout the semester, and then saying, right before the final, I don’t like what you’re doing with the stuff so I’m going to stop selling it to you. I’m just not sure how much sympathy you deserve.

Would that it ended with bad tactics. The entire basis of Anthropic’s government cooperation is actually ethically problematic, well beyond any reasonable allowance. Because the Claude-US. government deal comes via a partnership with Palantir — pretty much the most ethically challenged government-affiliated company you’ll find.

Palantir, which last year signed a $10 billion deal with the Army among other government departments, is beset with all kinds of moral challenges, which you can read about here and here and here and here, from mining our data to help ICE agents find people to target to plenty of other eye-popping use cases. As Robert Reich said recently , The AI surveillance state is real — and it’s being built by Palantir.” At some point the company doesn’t even deny it — it derives its name from Tolkien’s “palantiri,” orbs that let users see anything happening anywhere in the world at any time.

These are the people Anthropic has allied itself with?? The “safe” AI firm thinks they should be its partners??? A user on the ClaudeAI Reddit put it well: “I think it’s important to remember that the company that positions it self as the responsible and safe AI company is actively working with a company that used an app to let ICE search HIPAA protected documents of millions of people to find targets.” All a very curious thing to do for an Anthropic that since 2023 has soberly pledged, via a document called the Responsible Scaling Policy (RSP), to engage in something “analogous to the pre-market testing and safety feature design conducted in the automotive or aviation industry, where the goal is to rigorously demonstrate the safety of a product before it is released onto the market.” Those words will never be applied to Palantir.

And as it turns out, here’s the kicker — they’re not applied to Anthropic anymore either! Just this week — literally within hours of Amodei meeting with Hegseth — Anthropic was announcing that it was dropping that pledge. As Time Magazine, which was handed the announcement, noted, “[I]n recent months the company decided to radically overhaul the RSP. That decision included scrapping the promise to not release AI models if Anthropic can’t guarantee proper risk mitigations in advance.

“‘We felt that it wouldn’t actually help anyone for us to stop training AI models,’” Anthropic’s chief science officer Jared Kaplan told TIME in an exclusive interview. ‘We didn’t really feel, with the rapid advance of AI, that it made sense for us to make unilateral commitments…if competitors are blazing ahead.’”

None of this makes Anthropic sound like the good guys in the Hegseth-Amodei showdown. In fact, it scrambles our whole metaphor. This isn’t the dutiful nerd trying to do his calculus homework when the bully comes along. This is the disaffected evil nerd trying to create a chemical formula to blow up the gym, and the bully comes along and says, hey, give it to us so we can blow up a classroom.

There is some nuance, yes. Anthropic is trying to thread the needle, just saying there is no definitive testing doesn’t mean their models will actively be licensed to bad actors, etc. But man, it’s hard to position yourself as the safe one when you seem to be doing so much to toss out any semblance of safety.

All of which leads to the question of how this will shake out. Normally in a Trump-civil sector showdown there is a chance the civil sector wins. Not always and maybe not for long. But when you have a good-faith effort to stop the administration from dictating your university research or preventing you from suing the federal government, you could ostensibly succeed, and sometimes you do.

We have a lot less reason for confidence here. A tech company with powerful AI that enables mass surveillance and autonomous weapons has made a deal with both a giant government contractor and an administration that pretty clearly wants to engage in both those pursuits, and now it’s acting surprised the government wants to do those things? This didn’t occur to you before? It’s hard to take Anthropic’s affrontery all that seriously, and thus it’s hard to take their commitment all that seriously. And so even if Hegseth temporarily backs down, as he could Friday evening, there is little reason to think the safeguard-drop won’t happen anyway down the road or happen informally or happen piecemeal or happen somehow or another.

Anthropic has showed time and again, as it just did again this week, that while safety is something it cares about, it also won’t hesitate to put it in the back seat if competitive pressures and lucrative deals come calling. All the performative showdowns with all the world’s bullies doesn’t change that underlying truth. You can win the news cycle and lose the war.

2. WE’VE WRITTEN A LOT ABOUT HOW AI CAN DISRUPT THE JOB MARKET. IN FACT, WE’VE WRITTEN HOW DARIO AMODEI HIMSELF THINKS IT CAN DISRUPT THE JOB MARKET. (Some 20 percent of all jobs will eventually be disappeared, he’s said.)

But we’ve rarely encountered such a hard core example of it until today. That’s when Block, the Jack Dorsey-led company behind Square and the Cash app, said it would eliminate 40 percent of all jobs, some 4,000 out of 10,000 bodies, thanks to AI. “A significantly smaller team, using the tools we’re building, can do more and do it better,” the ex-Twitter chief wrote in a shareholder letter. On an analyst call Block CFO Amrita Ahuja said, “We see an opportunity to move faster with smaller, highly talented teams using AI to automate more work.

Dorsey even offered a prediction: “Within the next year, I believe the majority of companies will reach the same conclusion and make similar structural changes.” The comments particularly hit home because so much of what Block does is tech-related and these cuts touch on current fears of coders’ jobs going away — a codal panic — and because Dorsey is generally the kind of guy who sees what’s coming, as evidenced by him anticipating social media’s utility as a town square years before most people had thought about it that way.

They also hit home because of something else Dorsey said. We’ve known about the ways AI has already been a factor in layoffs — known by anecdote and by data. But until now most of the companies that have eliminated positions due to AI have done so prospectively — they were eliminating positions in anticipation of what AI could do, not because AI was already doing it. A Harvard Business School study of more than 1,000 executives published last month found that this was overwhelmingly the case. But Dorsey says the efficiency is already happening, right here right now. “Something has changed,” he posted on X. (He did contradict himself slightly when he went on to say in the post that he “could have cut gradually over months or years as this shift plays out.”)

That all delivers a blow that cannot easily be absorbed. But there’s something else troubling happening here that has nothing to do with AI and what it can or can’t do. It has to do with Dorsey.

Specifically, it has to do with the kind of AI job-loss normalization he’s engaging in. There’s always been a fear that penny-pinching CEOs would try to get rid of a bunch of jobs and then lay the blame on AI. “Don’t blame me, blame the machine” — one more way computer circuitry lets humans dodge accountability. But few of those CEOs are as future-credible as Dorsey. And few of them have set the bar so high (low) in terms of how many people they are publicly willing to part with. Every other CEO right now is looking at what Dorsey is doing and thinking is “If he can run his company with half his current employees, maybe I can too?”

They’re looking at Dorsey and thinking “If he’s so good at predicting the future and now isn’t worried about going into it with half his employees, maybe I shouldn’t be either?”

And — this may be most important — Wall Street is looking at Dorsey and saying “If he can make do with half his current employees in this age of AI, why can’t all these other companies?” And so they pressure the ones that can’t. (The Block share price was already up 20 percent after Dorsey made the announcement.)

I have no idea if Block as it currently exists can really be run just as well with 6,000 employees and some machine models as it could with 10,000 employees and no machine models. But it doesn’t really matter. Dorsey thinks it can. And that, sadly, will make a lot of other executives think they can too.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. 2025 ended on an up note, but the score for the year was dismal — a horrendous -42.5. Can we turn things around in 2026? So far, so ick.

DARIO AMODEI’S STAND AGAINST PETE HEGSETH IS PROBABLY JUST PRELUDE TO THE MILITARY GETTING TO USE THE TECH FOR MASS SURVEILLANCE AND AUTONOMOUS KILLING ANYWAY: -3.5

HALF THE EMPLOYEES? HALF THE PROBLEMS: -4.5

The Mind and Iron Totally Scientific Apocalypse Score for the week:

-8.0

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-16.5

Every Thursday (or Monday) we come at you with all the tech and AI news your giant brain can handle. Please consider joining our mission.

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Having finally taken that long-delayed week off last Thursday, we weren’t going to come at you till this coming Thursday. But the news, it has a mind of its own. A mad mind. What a crazy few days it’s been, between Ruairi Robinson’s Tom Cruise-Brad Pitt videos; the release of Seedance 2.0 (aka TikTok Sora) that saw a whole bunch of similar posts to the Cruise one; that viral Rhett Reese post agreeing with Robinson about how cooked Hollywood is; that viral Matt Shumer post about “something big is happening;” and all the attendant hype, backlash, criticism and commentary in response.

So we’re coming at you early this week — why put off ‘til Thursday what you can do Monday — with an item unpacking it all. And then back at you next week with what will surely be another truckload of madness.

First, the future-world quote of the week. Gotta go Reese.

“My glass half empty view is that Hollywood is about to be revolutionized/decimated. If you truly think the Pitt v Cruise video is unimpressive slop, you’ve got nothing to worry about. But I’m shook.”

— ”Deadpool” screenwriter Rhett Reese capping a crazy few days of AI news by describing his worries

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Everything you do — and don’t — need to know in future-world this week

Top Stun, aka making sense of what is happening

1. I THOUGHT ABOUT STARTING OFF THIS POST BY FRAMING THE ISSUE — LARGE LANGUAGE MODELS CAN SUDDENLY DO ALL THIS CREATIVE WORK AND WHAT DOES THAT MEAN FOR THE FUTURE OF CREATORS (AND WORK)?

That is, after all, what the Cruise video and Shumer post and Reese handwring are suggesting. (Most of you likely know; if not, it started last week with the entrepreneur Shumer going viral by saying that “something big is happening” regarding what AI can now do for coding and creative work, comparing the imminent blindside to the onset of the pandemic; continued with a video in which deepfake Pitt and Cruise fight over Jeffrey Epstein; and wrapped with Reese saying it’s over for Hollywood.)

But then, any good creative would know that you show, you don’t tell. So I give you this experiment:

About a day after Robinson’s Pitt-Cruise deepfake videos ran rampant (one of the clips right below if you haven’t see it), my THR colleague James Hibberd wrote a story about the news event.

As you can see from the below screenshots excerpting the piece, the story was a fairly straightforward tale of an AI video doing the impossible, hypesters nodding along, and worried Hollywooders like Rhett Reese wondering if this is the end. James did a fine job capturing what was happening, as you can see.

In short, he had engaged in the kind of blocking-and-tackling creative work that, if the hypesters are right, shouldn’t be that hard for AI itself to replicate. After all, if Generative AI was capable of so much magnificence beyond the Pitt-Cruise video — if, as the Shumer post said, great writing, like coding and accounting and consulting and designing, is now in a state wherein “I describe what I want built, in plain English, and it just… appears. Not a rough draft I need to fix. The finished thing” — then surely AI could handle a simple news article about those changes.

So I prompted Claude thusly:

Write a 15-paragraph news story about Ruairi Robinson’s viral AI video featuring a fight between Tom Cruise and Brad Pitt, also including the warning of Rhett Reese and the viral warning from Matt Shumer.

And got this in return:

In case you don’t want to read through that screenshot, I’ll (non-AI) summarize it and the rest of the story it yielded.

The Claude-generated piece started out OK enough, noting that “In a stunning display of technological prowess, filmmaker Ruairi Robinson has taken the internet by storm with his latest viral video, which features an intense and imaginative showdown between Hollywood heavyweights Tom Cruise and Brad Pitt.”

But it quickly went off the rails. It cited an “exclusive interview” with Robinson in which he said “The technology we have today allows us to push boundaries we never thought possible. Creating this fight scene was both a challenge and a thrill.” (He gave no such interview.) It went on to note that “many fans are thrilled to see their favorite stars in a fictional conflict” (that wasn’t the reaction many of any group were having).

Then it went completely bonkers, citing Reese as saying “’while it’s incredible what technology can do, we must tread carefully’” and that he “emphasized that such advancements could blur the lines between reality and fiction” (not even close); noted that “comedian Matt Shumer also went viral with a humorous yet serious warning...’Next thing you know, we’ll have an AI making a movie about AI making movies!’” (complete insanity); and also cited a word-salad quote about how we must “not lose sight of ethics as we embrace new technologies” from the film critic Janice Martin (a completely made-up person).

I then asked Claude to rewrite the article without the fake quotes. So it went on and reprinted basically the same thing, only without the quote marks.

You don’t need me to underscore the irony here: for a whole news cycle about the creative power and cleanliness of new AI models, an AI couldn’t write a simple news story without sounding like a super-lazy tenth-grader trying to get away with not reading the book.

So how do we square this? How do we square the admittedly realistic-looking Cruise-Pitt video — Reese is not crazy — and at least an inkling of what Shumer (an AI investor and hypester who should be taken with Lot’s wife-level salt) is getting at, with the simple fact that if full creativity is really within the reach of 2026 models then this news article I ran as an experiment shouldn’t be so laughably bad.

Or put more bluntly: should creative professions be worried or not worried?

The reality, of course, is that current models can do some things well and a lot of things less well. But how do we carve those distinctions? I think one way to think about it is like this: Current AI models can do, for a lack of a better term, snapshots. It can create a single moment in a piece of creative work that more or less seems passable, or, if our favorite stars are involved, even briefly eye-catching. So it can do a 20-second fight scene. It can do a decent first-paragraph of a news story.

What is can’t do is build off that. An AI model doesn’t understand flow, it doesn’t understand context, it doesn’t understand idea-development and it certainly doesn’t understand emotion or imagination. So it can’t really do much beyond that snapshot — ie, it can’t really develop a whole new story off that premise without giving nonsense thoughts or inventing quotes that just seem like they should be there. And it can’t really create a story off the fight scene. It’s interesting — we’re all taken by the video as it hints at a larger Russian conspiracy involving Epstein, as Cruise and Pitt are arguing about. But that’s our own human experience filling in the blanks — we’ve seen a lot of human-created stories of which this scene might be a part, so we imagine the machine is doing/can do this too. But there’s no evidence that a model has told or can tell anything close to the “Mission: Impossible” story that’s hinted at here. It can only do the teaser trailer.

Partly this is due simply to models struggling as length grows. But more fundamentally it has to do with how these systems learn. Some of the old, pre-LLM AI approaches, such as the so-called “symbolic approach,” tried to understand a realm in its entirety. They didn’t generally do it well, but that was the goal.

But an LLM, as you have no doubt heard, very much operate on predicting the next sequence correctly — the most likely next word or movement. That makes it particularly prone to missing the bigger picture; that makes it a lot more likely to execute what happens to Pitt’s face after Cruise throws a blow, and a lot less likely to be able to lay out a set of plot circumstances for why the blows are happening in the first place. Prompt Seedance to create a video explaining why two action heroes would be fighting over the fictious murder of a Jeffrey Epstein type and I suspect you’d get the same disjointed gibberish as you get when the prompted news story tried to move on from the fact of the video to the more complex sequence of reactions to it.

In fact I more than suspect it. I tried it.

“Create a 30-second video in which an action hero explains to a group of intelligence agents the geopolitical reasons a prominent human trafficker needed to be killed,” I prompted Seedance. (It wasn’t, for the moment, accepting famous names.) This is what it returned (at these exact eight seconds).

A perfectly fine anonymous snippet from a movie or show about some dude named Volkov who was doing bad things and needed to be eliminated. But there’s no machine-based way any of that could connect to the preceding scene I was playing off of — for that you’d need a human screenwriter to actually invent and shape the thing. You’d need, well, Rhett Reese, who far from being shook would be getting paid.

Storytelling, whether filmic or news-ic, is about building a large whole out of non-contiguous parts — anyone who’s ever assembled a piece of journalism or cinema will tell you this — and AI is very, very bad at this, just by the limitations of its design.

Now, you could have a human assembling these component parts, but at that point it doesn’t seem like the AI is doing much work — I mean anyone looking to replace a reporter would find the reporter is still very much needed for anything beyond the very limited utility of writing some initial factual sentences, just as any filmmaker would be needed for anything beyond a basic 30-second fight scene. The AI generation here is certainly not Shumer’s “finished thing.” In fact as a reporter in this case, if you tried to file what Claude generated the only thing finished would be you.

The final irony is what gave Shumer’s post its viral power was the comparison to covid and the collective naivete we all felt that February six years ago — exactly the kind of storytelling flourish and understanding of human emotions that an AI could never manage.

Perhaps the most potent explanation of this phenomenon comes from the AI skeptic and friend o’ the pod Gary Marcus, who noted in response to the video that these systems “struggle to reason…they were built for mimicry.” (He is invoking this characterization to urge a social-action campaign to outlaw “counterfeiting” humans and prevent scams, which of course mainly need just snapshots.)

Marcus also had an epic post refuting Shumer, noting, among other salient points, that “Shumer’s blog post is weaponized hype, filled with vivid narrative and marketing speech, but stumbles on the facts, especially with respect to reliability. He gives no actual data to support this claim that the latest coding systems can (reliably) write ‘perfect’ whole complex apps without making errors.” The “whole complex” apps is the thing — it can just do floating isolated pieces.

I’m actually surprised Reese missed this critical point of snapshot vs. storytelling as someone who has very adeptly done the latter himself; he’s focused on a clip from the movie and not what actually making one takes or feels like. But maybe he does get it, because in one of his posts he alludes to how a lot of the AI generations “will suck” and only if someone manipulating it “possesses Christopher Nolan’s talent and taste then it will be tremendous.” Which kind of undercuts his whole point about how over everything is, and underscores our point above: all it can really do is snapshots. For everything else you need a flesh-and-blood Christopher Nolan. Exactly like you need right now.

I know, the whole subject can be head-spinning. What can AI really do, what’s its ceiling, what’s our floor. Here’s what matters. The technical component of creativity is indeed getting better and better; you’d have to be blind not to see it. Physical shoots are undoubtedly going to become less common. There’s no way around that. But logic, facts, imagination, continuity — ie, everything that makes a film a story and not just a collection of images, or a news story a story and not just a collection of statements — is still stuck in the present gear, and I believe will be for a long while. So is something big happening? Sure, if your job is technical. For everyone else, I’d say what’s happening is small-medium. Which the AI would be quick to tell you is a fine T-shirt size.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. 2025 ended on an up note, but the score for the year was dismal — a horrendous -42.5. Can we turn things around in 2026? So far, not too great.

AI CAN CREATE SOME REALLY COOL VIDEO BUT STILL CAN’T TELL THE MOST BASIC STORY: -2.0

The Mind and Iron Totally Scientific Apocalypse Score for the week:

-2.0

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-8.5

Every Thursday we give you the best (and sometimes worst) of what AI and the future hold. Please consider joining our community.

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We’re hitting you in a cool way today, as there were three notable developments over the past week that all seemed different but are actually unexpectedly connected.

Among them: Apple buying a startup that holds a patent for “facial skin micromovement” — ie, a kind of detection that eliminates the need for communication as we know it. A Valentine’s Day AI plan that eliminates the need for relationships as we know it. And a Super Bowl ad that eliminates the notion of actors as we know it. AI, it’s playing the elimination game!

We’ll tie all these together and propose some thoughts on what they tell us about the future.

And again, as we keep the issues pouring in, we may or may not take a break coming into President’s Weekend next Thursday.

First, the future-world quote of the week:

“Enjoy a romantic rendezvous with your AI partner in a cozy, dimly lit atmosphere.”

— The craziest Valentine’s Day ad you’ve ever seen

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Let’s get to the messy business of building the future.

IronSupplement

Everything you do — and don’t — need to know in future-world this week

Speaking, watching, loving with AI; Do we want all this?

1. I ADMIT TO CHECKING MY CALENDAR WHEN THE NEWS RELEASE CAME INTO MY INBOX: WAS IT APRIL FOOL’S ALREADY?

I can’t even begin to describe this newfangled piece of crazyroo, so I’ll just quote the message:

“For many, AI companions have become a meaningful part of their lives, helping them cope with loneliness, overcome life challenges, or just make it through a stressful day. Though AI chatbots have been around for a while, the only way of interacting with them has been through texting. Going out, sharing a dinner, or even having a heartfelt live chat with one’s AI partner still sounded like a sci-fi fantasy.

Until now.

EVA AI, a relationship RPG app, brings the fantasy to reality, opening the EVA AI Café. This is another step in the company’s long-term strategy to push the boundaries of interaction with AI and make AI relationships a new normal. At the cafe, visitors will be able to:

• Enjoy a romantic rendezvous with their AI partners in a cozy, dimly lit atmosphere.

• Have a speed date with one of the custom-developed AI companions;

• Test EVA’s new voice-chatting feature, allowing users to talk to their animated AI partners live – a unique tech advancement, never seen at any AI platform before.”

So yes, if you’re already in deep with an AI paramour but still want to go out and celebrate with the whole candlelight and fancy-restaurant schmear — that is, if you want to indulge in screen-hiding behavior in extremis while still doing in-person gathering in normalus, feel not conflicted anymore. Just take your AI date to a restaurant. What happens there and how you avoid an international incident, the release did not say. But now you have options.

(If you’re curious, EVA AI claims to let you “Meet your ideal AI partner who listens, supports all your desires and is always in touch with you.” There’s apparently a long-running debate on where it stands in the realm of AI companions.)

That’s the first development. I’d say it only gets crazier but from here, but I don’t think that’s possible. (OK more seriously, this kind of thing does make sense. AI companions are going to become increasingly popular no matter how clearly bad and humanity-destroying they might be, and it stands to reason that as they become popular there will be services that take them into new modalities. Whether they take them there well is another matter.)

The second development is a Super Bowl ad airing Sunday that was created pretty much all in AI. It comes from the vodka brand Svedka, which wanted to forge an aesthetic that fit its Fembot and Brobot mascots. I talked to the chief marketing officer of Svedka parent Sazerac for THR this week, and she said that while everything (including the very human-looking dancers behind the robots) were generated by AI, there really is a human message underlying the spot.

“The entire idea of the campaign is that the robots have returned to remind the humans to be more human,” the executive, Sara Saunders, told me over at THR. “Our message is ultimately pro-human.” The robots do short-circuit when they try to party like humans, and the humans are dancing IRL like we used to do in the old days, before dancing became something we do for likes in front of a camera.

But that message may be lost, or at least tempered, by the fact that no human actors were involved in the making of the spot, and the overall aesthetic has a general uncanny-valley vibe, a la the Revolution War Aronofsky characters last week. All of which could lead to a backlash. “We expect it and we welcome it,” Sanders says. That’s refreshing at least — it’s nice when an executive is honest about what’s coming.

Finally there’s this: Apple purchased Q.ai, an Israeli startup that is focusing on all kinds of emotion-detection and facial-sensing.

Q.ai “is a remarkable company that is pioneering new and creative ways to use imaging and machine learning,” Apple’s senior vice president of hardware technologies Johny Srouji said in a statement. But that doesn’t fully convey what the firm can do.

What is that? In a word. Sensing. Based on your expressions. (Or in techno-lingo, “facial skin micromovements”)

Q.ai has about 100 employees and is led by chief executive Aviad Maizels, who previously founded a company that Apple previously bought which paved the way to facial recognition on your iPhone. This new firm levels up all that sensing, making it so that facial movements don’t just unlock your phone but send messages and convey emotion while you’re on it; imagine, in one very small use case, not selecting the eyeroll emoji but simply eyerolling in a way the other person picks up. Messaging is no longer about typing or leaving voice notes — it’s about simply reacting, human-style.

The tech also could, according to its creators, assess emotions in our faces in broader ways, which could be used for everything from marketing focus groups to therapy apps. Basically if you can feel it (and exhibit that feeling), Q.ai’s tech says it can know it.

Maizels, who will continue to run the company in Cook-land, says that the sale will only super-charge its efforts. “Joining Apple opens extraordinary possibilities for pushing boundaries and realizing the full potential of what we’ve created, and we’re thrilled to bring these experiences to people everywhere.” It is, if nothing else, about to be brought.

Three crazy innovations, all announced in the same week. Three innovations bearing down upon us. But how to think about them?

2. WHEN DO “EFFICIENCY TOOLS” JUST BECOME JOY-SAPPING SHORTCUTS? When does a desire to avoid the tedium cut out all the part that quietly makes something meaningful in the first place?

The history of tech is at heart a history of eliminating the labor and time that previous generations experienced as a matter of course — longhanding a letter and waiting for its delivery three days later vs. getting a thought and speaking it into a voice note for delivery three seconds later. Not many of us, even the nostalgists, would sign up for a return to that particular world if it was offered to us right now.

In that regard tech enthusiasts are correct when they say that it’s neither fruitful nor wise to protest (”no generation of human beings has ever been able to stand in the way of technological advances — it happens,” as Bob Iger told David Muir this week). I mean, he’s right. That thought has been accurate. But emphasis on the has. Because there is an end point to the convenience train. If we take this logic of technological progress and automation to its extreme, after all, no act ever would be worth undertaking and toiling through, which leads to “Wall-E” and a complete shutoff not only of any kind of human thinking or effort but any joy that can result. I don’t believe many of us (let alone mental-health professionals) would sign on for that. And so the question becomes when does the added convenience start to take away more than it gives?

What is the right point, in other words, to stop between voice notes and “Wall-E?”

Is the idea of simply showing a device your emotion instead of trying to know and characterize it that point? Maybe. Most of us I suspect would quickly get used to this new reality. Is eschewing the hand-made art in favor of something a machine could do that point? Certainly those of us who earn a wage using those hands would say yes, but I suspect many of us who are simply consumers will, for all our discomfort now, eventually shift our standards and drop our protests as this automated stuff becomes more integrated into our visual lives.

Is a programmable AI that allows us to pretend we’re engaging emotionally without the unpredictability and mess of a human relationship that point? Certainly many of us think that crosses the line — the back and forth of a relationship, difficult as it can be, is what makes a it worth having in the first place. If you don’t struggle to align, how rewarding will a machine-enabled alignment actually feel? That’s why our gut instinct is to mock the idea of an AI Valentine’s Day date; it’s not just sadism. But the truth is that even such a development might experience a goalpost-move, and these kinds of seemingly unconscionable shortcuts (you’re just going to code your way to a happy partnership?) could seem more and more conscionable as time goes on.

I guess my point is that we’re all going to have to decide where that line lies, individually and collectively. It’s OK to set it far away or close by or anywhere else we deem right— anyone who tells you there’s a universally correct place to put it is naive or lying. But wherever we set it, I think we need to be firm about it, and then push back on tech companies with everything from downvotes to tune-outs when an innovation crosses it — to say definitively that this, finally, gets us too close to the “Wall-E” zone.

On Sunday during the Super Bowl, a whole bunch of companies, from Google to OpenAI to Amazon to Anthropic to plenty of non-tech brands, will offer their vision for the future. They’ll present it all as shiny fantasies that will inevitably descend upon us. Neither, of course, is accurate. What they’re selling isn’t always shiny and it’s certainly not inevitable. There is a line between convenience and laziness, between an easier human life and a fully automated one. All these developments try to push that line. But we should remember that where we draw it is always up to us, if we want it to be.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. 2025 ended on an up note, but the score for the year was dismal — a horrendous -42.5. Can we turn things around in 2026? So far, not terrific.

VALENTINE’S DAY CAFES FOR AI COMPANIONS? You for real right now? -3.0

AI-GENERATED COMMERCIALS: -2.0

TECH THAT LETS US EYEROLL INSTEAD OF EMOJI: Actual Eyeroll -1.0

THE ABILITY TO PUSH BACK ON ALL OF THIS: +6.5

The Mind and Iron Totally Scientific Apocalypse Score for the week:

+0.5

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-6.5

Every Thursday we come at you with all the AI and future-y news you need to know. Please consider joining our community.

Subscribe now

We originally thought we might be taking a break this week. But we just can’t quit you. Plus, you know, the news. So we’re back at you today and will punt our week away either to next week or the one following.

To wit, re said news, a major filmmaker — one Darren Aronofsky — announced a big new AI project with Time Magazine, the defining media outlet of last century with the major tech of this one. We wrote the news story for THR today, and we’ll expand further on what it means in this space.

Also, corporate espionage is about to get crunk. Actually, it’s already crunk, judging by the conviction Thursday of a Chinese national who worked as a Google engineer and had been charged in San Francisco with theft and other crimes. His sentence can run up to 175 years in prison — he’ll need a lot of Bryan Johnson immortality pills to outlive that one. We’ll tell you why you should care and why we’re about to see the temperature go way up on cases like these.

First, the future-world quote of the week:

“This project is a glimpse at what thoughtful, creative, artist-led use of AI can look like — not replacing craft, but expanding what’s possible and allowing storytellers to go places they simply couldn’t before.

— Time Studios president Ben Bitonti, on why he thinks AI will allow us to plunge into history anew

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Let’s get to the messy business of building the future.

IronSupplement

Everything you do — and don’t — need to know in future-world this week

Washington, Franklin, Hamilton, Hinton; Spies Like Leon

1. IF WE COULD UNDERSTAND HISTORY BETTER THROUGH AI, SHOULD WE? Or, put another way, with all the tools we’re getting every day to dream images into being, should we be using them to understand our past?

So gambles a bold project announced Thursday by Darren Aronofsky, the longtime U.S. auteur who never fails to experiment or entertain. No doubt you know and likely love at least some of his films. As I reported in THR, Aronofsky announced a weekly series for all of 2026, distributed on Time’s YouTube channel, dramatizing key Revolution War-era moments that happened 250 years ago, on the day of the episode’s release.

“On This Day...1776,” as it’s called, will seek to explain how the Revolutionary War was not a given and leaders and ordinary people had to fight to make it happen. The catch is Aronofsky didn’t shoot any of the episodes: he and his team designed them using the tools of Google DeepMind and other companies, everything from the scenes to the actors. Only the voices involved humans.

The premise, just purely on a social level, is fascinating. Bringing history to life for cinema or a TV show is laborious and expensive; it’s why we get these projects rarely and, with a contraction of Hollywood original content, even more rarely soon enough. Enter AI, which can sidestep all those lavish requirements of shooting a historical drama and (its proponents claim) bring these scenes immediately to life to enlighten and educate. Blam-o, our country’s history-education crisis solved. Well maybe not. But ameliorated.

Anyway, Aronofsky has been defying the AI binaries for a while — he’s not shunning it, but he’s also embracing it carefully, saying that his venture Primordial Soup aims for “soup not slop.” He’s trying to use AI to tell rousing stories that look like cinema, and that make you feel. And so here is where he ended up. You can watch the first episode here and the second here. This is the trailer:

Some of the YouTube comments were brutal (”This is great! I hate life and beauty!!”) and it’s understandable why. We’re conditioned to think about period filmmaking as a result of physical production — someone spent a lot of effort to design productions, dress actors, hire crew and then haul them all to somewhere tax-friendly to have scenes re-enacted in front of cameras. That process comes with a certain authenticity we just don’t get with AI videos.

Or should I say, it comes with an inauthenticity that we’re used to. Actors standing in front of a camera reading lines are, no matter how persuasive, a kind of stylization too, along with costumes, set design and other accouterments that we only believe are real because we’ve suspended our disbelief so many times before. It’s not that movies are unreservedly authentic. It’s just that we’re pretty accustomed to the tricks.

Now, I’m not going to claim these AI tricks are good enough to fool us on their own. They’re not. Far from it. The faces can have a certain sameness of expression and the dialogue doesn’t always neatly sync, which is one reason Aronofsky cuts quickly and tends to show more close-ups of objects. But I do think we’ll mind these flaws less as we see them more. Also the tech will get better. I don’t know if we can ever get synthetic actors who don’t look dead behind the eyes. Can a creation trained only on what came before give the spark that we recognize when we see a worthy human? It’s an interesting technical, and philosophical, question. But they’ll almost certainly look more like humans than the current crop does.

I guess what I’m saying is it feels right to leave aside some of the skepticism. That’s not because we don’t want to turn into Bryant Gumbel (”What Is AI?”) a la that famous “Today” video from the mid-90’s, though we probably don’t. It’s because we tend to underestimate new tech on multiple fronts — how primitive it will soon seem compared to where it goes and how naive we will seem compared to where we will go. Maybe slop always remains slop and YouTube comments on videos like this always remain overwhelmingly snarky. I suspect not though. I suspect it looks better and we care less. Which would mean — at least theoretically — that we’re left with important topics in the hands of good filmmakers who can give us something they never could have given us before.

That does raise one last question. Well, two. First, would we get a great filmmaker if they come of age in a world where they’re not shooting these movies? Aronofsky knows what to do with AI cinema in part because he made “Pi” and “mother!” and “Black Swan” and “Requiem for a Dream.” Would an aspiring director raised only on Cahiers du DeepMind have the same aptitude? Unclear.

And, second, maybe in some cases they give us what they couldn’t have before; I could see Aronofsky struggling to get a 50-part Revolutionary War series financed, and AI stepping in to solve the problem. But there are plenty of films that someone would finance in a traditional physical way until someone offers them an alternative, in which case they might just say “eh, do it in AI” and then we don’t get it at all. Do epics like “Noah” or tough sells like “The Wrestler” and “The Whale,” to stay on theme, get made in an era when a studio or financier could just say, nah, it’s not worth all that physical production; we have an alternative? There’s a law of unintended consequences here. It’s easy to say that AI will bring all these unmakeable films into existence. What the tech’s advocates don’t tell you is all the makeable films that will never see the light of day.

So what to think about the idea of prestige drama being put through the AI machine? It’s complicated. But as of today’s drop, it’s here. And probably soon charging at us faster than Washington at the Battle of Princeton.

2. IF YOU SWIPED SOME PENS AND PAPER CLIPS from your last job before leaving and felt guilty about it, imagine how this guy feels.

This guy would be Linwei “Leon” Ding, who after five years at Google abruptly left his job in 2024 with a one-way trip to Beijing. Also coming with him, along with the snow globes of the Golden Gate Bridge? Some 2,000 pages of confidential Google info.

Our boy Leon then turned around and pitched investors on/applied to a grant in China for a supercomputer that would “help China to have computing power infrastructure capabilities that are on par with the international level,” according to an application unearthed by the prosecution. A jury said he’ll have a jail sentence on par with the international level instead. On Thursday he was found guilty on seven counts of trade secrets theft and seven counts of economic espionage. He could do as much as 175 years.

Now, ol’ Leon may not be the shiniest jewel in the display case, nor his plan an especially wise one — for one thing, he kept all the stolen documents on a Google Cloud account. (!) Like robbing Chase and then opening a checking account to stash the money. But his efficacy aside, Leon’s plan is a telling one.

Corporate espionage is about to become a much bigger deal, because the stakes of AI are so high and because, well, countries around the world saw what the U.S. did with personal computing and microchips and smartphones and are not exactly in a mood to let that happen again. (That’s why China has been pouring so much into the effort, of course, but also why other places have been furiously looking for any spare change they can find to throw at the sector; the European Commission just allocated 300 million Euros to “bolster Europe’s digital innovation and competitiveness.”) As these countries get more invested, so too the tactics will get more underhanded. The U.S. Attorney’s office is currently investigating two similar Chinese-nationals-at-U.S.-tech-giants, both at Apple, for version of the same theft-y thing.

Nor is it just countries. The Justice Department last week opened an investigation into Deel, an HR startup, alleging that it recruited a spy working at its rival Rippling. The details of the case are hilariously petty — the spy, Rippling says, was searching databases many times each day in search of Deel customers who switched to Rippling, and then funneling the info back to his handler so Deel could understand what was luring them away. Hilariously petty, that is, until you realize that Deel is valued at $17 billion.

The tech world is increasingly seen as a place where there’s only one winner in a given sector — we all livin’ in an Oligopoly world — and so companies are more motivated than ever to be as ruthless as they can get away with.

This would be unnerving and icky enough even if it wouldn’t affect all of us. But it will. Because many of the companies WE work for will be subject to the same problems — or more specifically, the paranoia about those problems. Right now most of us are told to be careful on company communications channels. But the oversight and anxiety is about to get upped to eleven.

A friend who works at a big bank said she doesn’t even like getting harmless emails because of how they can be scrutinized by the overlords. (AI will make the scrutiny easier, and thus the problem worse.)

And the Deel case, interestingly, was cracked because Rippling put out a Slack honeypot — executives claimed to a bunch of employees (including the suspect) that there was a Slack channel in which people can discuss defecting Deel customers (the channel was a Potemkin Village), then watched as the alleged spy furiously searched its empty spaces. Kinda brilliant actually. But an example of how regular office tools will increasingly become a way for corporations to determine loyalty. And while of course 99.9 percent of us are feeding competitors nada, the mere possibility that someone is means that bosses will be looking at all of us. And once they’re looking, who knows what they’ll find.

So poor Leon, it turns out, is just the tip of the berg. He may have swiped 2,000 documents. The rest of us will soon have to worry about who’s looking at ours.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. 2025 ended on an up note, but the score for the year was dismal — a horrendous -42.5. Can we turn things around in 2026? So far, eh.

I CANNOT TELL AI: THE TECH TURNS TO GEORGE WASHINGTON +1.0

CORPORATIONS ‘BOUT TO GO SPY CRAZY: -2.5

The Mind and Iron Totally Scientific Apocalypse Score for the week:

-1.5

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-7.0

Every Thursday we bring you the essentials on AI and our shapeshifting future. Join our effort here.

Subscribe now

There are busy news weeks and then there are weeks like this one. In the span of a few days we got some big news about Apple AI hardware, some other big news of an Anthropic “Constitution” (really, they called it this) and on top of all that perhaps the most exciting use of Gen AI music yet (that also showed it limitations). We got it all for you.

Quick housekeeping note we may or may not be taking a quick break next Thursday; we’ll know then, and so will you. But don’t worry, we’ll give you an extra chewy episode today.

First, the future-world quote of the week:

“We want Claude to have a settled, secure sense of its own identity.”

— (An AI company actually said this?)

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Let’s get to the messy business of building the future.

IronSupplement

Everything you do — and don’t — need to know in future-world this week

If you like it then you shoulda put a pin on it; Tip your hat to the new Constitution; AI is just somebody that we used to know

1. A STAR TREK-CENTRIC FRIEND LIKES TO SAY THAT any technology worth having has been prefigured on the show, from the tablet-like PADDs to the Zoom-like communications screens to those 3D-printing replicators.

The latest piece of tech to make Gene Roddenberry look prescient? The “combadge” — or as we moderns call it, the AI pin. You know, that little adornment that Starfleet personnel wore and touched when they wanted to speak a command and was integrated into the show the way, well, some companies want to integrate it into our lives.

This week by far the biggest of such companies joined the game. The Information reported Wednesday that Apple has been developing precisely this item. Its little flat disc (apple?) will contain cameras and do a lot of what our AI-enabled smartphones will be able to do but with more seamless integration — SV-speak for you’ll be able to use natural language to engage with it. Siri, but with the latest LLMs.

The interface is the thing here. Instead of all these AI apps like booking that ticket to the museum or summarizing the text from the exhibit (apparently we’ll have a lot of time to go to museums in the AI age) just swimming around on our phones, we’ll be speaking them into existence on our lapels. The company is planning on 20 million units and could have them ready as soon as next year.

So how to think about a development that seems both incremental and kind of futuristic? Well first, worth remembering that the current way we interact digitally, the smartphone, is really just an accident of technology. What we actually like of course is the convenience of being able to read, buy, message, learn, share and watch on command. The idea that this happens when we pull a moderately thick rectangle of our pockets is just where the technology happened to land. There’s no inherent reason for this pocket-inhabiting form. And the iPin is here to make the point.

That’s the rationale, anyway. But the news is curious for several reasons. The first is just the corporate irony: as Apple is making moves into AI, OpenAI is making moves into Apple. You may recall how last spring OpenAI spent many billions of dollars to buy the company of Jony Ive and hire him to bring the same iPhone magic to their precincts. So Apple is coming at it a little late and without the guy who has previously delivered the goods.

The second is more consequential: how many of these wearables have sputtered before? Startups like Humane AI and Rabbit haven’t taken off; Google Glass never took off; Ray Ban Metas have sorta kinda taken off. Most important, Apple wearables themselves have been a mixed bag. The Apple Watch has brought some added utility, but really only as a smaller phone with a strap, while AirPods are just its souped-up Bluetooth headphones. The Vision Pro hasn’t gone anywhere.

Now, it’s easy to dismiss any new wearable as so much corporate-foisted superfluousness; the nature of fresh hardware is we don’t see the appeal until after it’s ubiquitous. But there are legit reasons to be skeptical here.

One is that companies somehow keep confusing hardware for software — the device with what it can do. Google Glass looked coo’ but couldn’t get a basic recipe or direction right; Rabbit made big promises about that orange box but missed the mark again and again on its AI-assistant ambitions. We might have a little more hope for Apple given how singularly it has integrated software with hardware — how much it has brought us closer to having these machines do things that we need. But when you consider that it hasn’t churned out a massively popular new genre of hardware since, really, the iPad, optimism lind of leaves the room.

What will really make the pin take off is either that it can deliver AI that no other device can (an open question, and couldn’t that just be on a phone?) or that it could so forcefully do away with our current messy overlap of apps that we can’t but adopt it. We forget how, submerged in our Apple Store and Google Play worlds, technology was never supposed to give us this world of downloads and installations and openings and closings. All the things we use an app to do — all the ordering of food or booking a ride or looking for a date — were supposed to happen by merely speaking (or even thinking), and if you told someone 30 years ago tech could do all of those things but you needed to fiddle with a bunch of downloads and interfaces first they would have called you a nerd and asked why bother.

And so the pin comes to say — no mas. Stop with all the friction. Don’t even move your hands. Just speak and it shall be done. Now, I have no idea if an Apple pin can deliver this app-less seamlessness, let alone do so with the kind of intelligent AI that no operating system has yet to master. But that does feel like what needs to happen: Make life easier and our devices qualitatively better. An iPod that just played songs the usual way would be a cooler-looking Walkman. Endless storage, quick downloadability, musical ubiquity? Now we’re talking. The iPin would have to pull off the AI age equivalent.

And yet even if it could, I wonder whether we want this seamlessness. Tech companies may lament that the phone has to exist as a separate item. After all, everything about the history of devices suggests a growing smallness and closeness. We went from mainframes to personal computers to laptops to smartphones. And so why not a pin?

But what if, in this march to intimacy, we want to draw a line? What if the fact that a phone exists apart from us isn’t a bug to be solved but a virtue to be embraced? What if we subconsciously LIKE that we have to pull something out, because then it means we can put it down, or leave it in the other room, or somehow disengage with it — something that becomes much harder when it’s on our shirts. I don’t know that we feel this way, because most of us never stopped to ask. But with so many wearables failing, it starts to feel a little like seamlessness is a liability.

That it’s not so much that we haven’t embraced wearables because the right one hasn’t come along, but companies can’t sell us wearables because we don’t want to embrace them.

So we can focus on the design all we like, and we can extol Apple for all the ways it’s mastered this before. An iPin might just well be the latest “Star Trek” innovation to become commonplace in the 21st-century. Or it could be like a commemorative Starfleet souvenir: cool to look at, pointless to use.

2. AS WE SPEAK, THE FLORIDA LEGISLATURE IS DEBATING AN “AI BILL OF RIGHTS.” A surprisingly tough-minded set of regulations on what tech companies can and can’t unleash. But a different founding document — an AI “Constitution” — dropped this week, from a source you wouldn’t expect: Anthropic, the maker of code sensation Claude.

An executive at the company led the overhauling of an earlier (much more vague document): Amanda Askell, a kind of philosopher-coder who’s known internally as the Claude Whisperer. (Her literal socials bio: “Philosopher & ethicist trying to make AI be good.”) Anthropic has positioned itself as a more humane AI company, and Askell’s new Constitution for the company’s LLMs are meant to reflect that.

Some sample language to this updated document: “If we ask Claude to do something that seems inconsistent with being broadly ethical, or that seems to go against our own values, or if our own values seem misguided or mistaken in some way, we want Claude to push back and challenge us, and to feel free to act as a conscientious objector and refuse to help us.

“Just as a human soldier might refuse to fire on peaceful protesters, or an employee might refuse to violate anti-trust law, Claude should refuse to assist with actions that would help concentrate power in illegitimate ways. This is true even if the request comes from Anthropic itself.” (You can read the full James Madison document here.)

It’s a strange pretzel, trying to ask the AI to push back on human coders instead of just putting the onus on the coders — ie, the people building the thing and writing the Constitution. Indeed too much of the document seems to abdicate a human responsibility in favor of hoping a machine will supersede. I mean, isn’t it the humans who decide what to train it on? Or to build it in the first place?

In a similar vein, this Constitution doesn’t seem to be centering human feelings. If anything, it’s the opposite. It’s worried a lot more what we will do to it than what it will do to us (or, more accurately, what the people training it will do to us). Far too much of it seems to be rights…for the machine. “Claude’s wellbeing and psychological stability: We want Claude to have a settled, secure sense of its own identity,” it says, and if you didn’t know better you’d think it was a kindergarten teacher talking to parents about a kid named Claude.

Sure, some of the language frets over an AI’s effect on society . “Claude is mindful of its potential societal influence and prioritizes approaches that help people reason and evaluate evidence well, and that are likely to lead to a good epistemic ecosystem rather than excessive dependence on AI or a homogenization of views,” it says aspirationally. (Even there btw the guardrails seem unenforceable and contrary to the whole customizing point of an AI agent; am not sure how one plausibly avoids an AI that “provides serious uplift” to chaos-seekers.)

But the bigger problem is that a whole bunch of the language worries about society’s effect on AI. The document is filled with statements like “In creating Claude, Anthropic inevitably shapes Claude’s personality, identity, and self-perception...In some ways, this has analogies to parents raising a child or to cases where humans raise other animals.”

I had to laugh when in the opener the Askell and her team warned that “this covers various topics that may be of less interest to human readers.” Really? First, given how too much of AI still can’t tell a tomato from a clown nose am not sure we should be writing documents with that audience in mind. Also Anthropic’s whole spiel is about a more humane AI. And now they’re not writing documents for humans?

Seventy five years ago Isaac Asimov laid out (in the book titled “Mind and Iron”) the “Three of Laws of Robotics,” meant to protect humans from machines. Oddly what Anthropic has done here is lay out laws meant to protect machines from humans.

They do have a rationale for it. The company has advanced an idea about the value of being kind to another intelligence. Kindness is always a virtue, and coaxing more of it out of humans is never a bad thing. Except that’s really only a byproduct of what Anthropic is doing here; after all, if it was the primary goal they’d be encouraging everyone to join AmeriCorps. It can start to feel like the main objective, or at least the main outcome, is to make machines seem more cuddly and sentient so that we’re less skeptical of them. You don’t put guardrails around a trusted friend.

OK, perhaps not every action is so cynically calculated. But it’s hard to read lines like “Claude may have some functional version of emotions or feelings” and “we should lean into Claude having an identity and help it be positive and stable,” from a company that stands to make billions from the adoption of those technologies and not suspect they’re up to something.

As a redditor in the AI subreddit noted recently: “This focus on consciousness seems to be a deliberate strategy to anthropomorphize AI in the public eye. It distracts from the real ethical and safety concerns of AI, like bias, misinformation, and the potential for malicious use. Instead of addressing these immediate problems, Anthropic seems more interested in creating a mystique around their creations, leading people down a path of superstition about AI’s true nature.”

All of this comes as part of an Anthropic exploration into what it calls “model welfare” — basically, should we start preemptively worrying about a computer’s civil rights? (Earlier this year they even hired an executive to oversee it.) Hey, this handwringing could be one of those things that sounds crazy now but will one day be a given, if some kind of sentience is in fact achieved. Or it’s the kind of thing that will always sound crazy.

Anthropic is filled with more idealists than most AI companies (a number of its senior staff left OpenAI for this reason), but then, why build products that are meant to replace engineers – why not build, say, tools expressly to find cancer-fighting compounds or increase our odds against climate change? Executives will say that these tools can be deployed for drug discovery and climate change, and no doubt some will, but this hardly seems like their main objective. In fact, as with pretty much all for -profit tech companies there IS no main objective, beyond getting a lot of people to use their products. These models are optimized for usage, not beneficial outcomes. (One piece of evidence for this is that the company is not applying this Constitution to apps it is building for the U.S. military.)

Chasing usage over altruism is a company’s right, of course, just as it is advocates’ and government’s right to call them out for it. What gets crinkly is when a tech firm starts to pretend that’s not what they’re doing. Anthropic feels like a for-profit OpenAI trying to persuade us they’re still the nonprofit version. At some point it might just be better to become Sam Altman and own it.

It’s hard to know what effect this will all have on the ecosystem. Anthropic says it’s releasing the Constitution in the hope other companies adopt it, but one has a hard time imagining the world’s biggest tech firms putting shackles on themselves of even this airy-fairy sort. More likely they’ll pay lip service to humanism and the virtues of self-regulation and go right on with their business. After all the noise, that may be the doctrinal principle they believe in most.

3. IN THE EARLY 90’S IT WAS NATALIE COLE SINGING WITH HER LATE DAD NAT KING COLE.

In the late 2020’s it’s Elvis, Ozzy, Freddie Mercury, Kurt Cobain and Amy Winehouse singing a Gotye song. They’re all very much dead, of course, which is why the use of Generative AI was called for.

The latest AI mashup trend — oohed and ahhed at by the extremely online and, soon, no doubt, by a team of lawyers — has the Gotye song “Somebody That I Used to Know” sung in fragments by an ensemble of great artists (some live ones like Snoop, Eminem and Daft Punk are in there too) while their faces fracture and morph. You can watch it here.

As you can see, the video was posted (created?) by the Instagram influencer themusicaddiict and, for all the talk about slop, it does have a kind of mystical power, as a song is vocally reinterpreted in real time by some very diverse artists. (Am dating myself here but it gives “We Are The World,” with all those iconic voices each taking a lyric, sonic cacophony into beautiful jigsaw.) “This is the only acceptable use of AI,” the addiict posted, and while I don’t think it stands THAT far apart from some of the automated rehashes out there, I’d get why that would be the pitch.

I don’t think this stuff will have staying power — it feels a little like early celebrity deepfakes from the beginning of the 2010’s — but it does converge a few trends and hint a little at what’s to come. You may have seen the craze this past fall in which songs are covered in radically different genres (eg, 50 Cent as a hard rocker) via novelty-heavy channels like Almost Real. This ups the ante by broadening the artists and weaving them all into a single cover.

Much of AI-generated film and music is, as we all know, quite bad. As Ben Affleck said sitting next to Matt Damon on The Joe Rogan Experience last week: “If you try to get ChatGPT, Claude, or Gemini to write you something, it’s really shitty, because by its nature it goes to the mean, to the average.” But this GotyAI mashup actually feels quite clever. I found myself unable to take my eyes off what was happening, first spellbound by the sheer magic of all these different iconic voices and faces melding together, then contemplating more practically how he did it.

And yet it’s quite clever precisely because of the rehash — not Affleck’s regression to the mean, but not unrelated to it either. The whole thing only works because we know all these faces and all these voices and it’s cool to see them seem to record together — see them blended into Affleck’s average.

I guess if there’s a revelation here it’s that even that average — even a machine drafting on what was done before — can be interesting with the right concept and editing. I don’t know if that makes it art. And I certainly don’t know if there are new frontiers to push. But if you squint you can start to see the early shape of something cool. As we head into a world of mass-produced memeslop, of AI tools used to create music for labels and videos for Disney platforms, it’s encouraging to think that there are some interesting things can be done with it — that the slop, while hardly high in nutrients, might sometimes at least taste pretty good.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. 2025 ended on an up note, but the score for the year was dismal — a horrendous -42.5. Can we turn things around in 2026? So far, it’s middling.

A PIN YOU CAN’T PUT DOWN: -2.5

GET THOSE AI PRINCIPLES IN WRITING: Right idea, wrong execution -1.5

ACTUALLY SOME COOL AI MUSIC: +2.

The Mind and Iron Totally Scientific Apocalypse Score for the week:

-2.0

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-5.5

Every Thursday we bring you the necessary nuggets on AI and the future, and some ways to think about them. Please consider supporting our community.

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This week has seen plenty of key developments — and that’s apart from all the Grok nonconsensual-image madness (more on that another time, though we’ll just say we may finally have a truly impactful object lesson in what happens when you combine a lot of AI with very few guardrails).

One of this week’s developments comes in the realm of education. How much should we be teaching our kids with the help of AI and how much should we be dropping the tech faster than we drop the tutor who just hired a Hollywood agent and can’t stop going on auditions? The most prestigious think-tank around just did an impressive study on the subject of AI in childhood education. We’ll break down the results.

Also, how will institutions fare in the age of AI? I don’t mean mental institutions, though maybe them too. I mean institution institutions, the kind that protect democracy. Some crucial new intel there, and we’ll fill you in on what’s been revealed and a way to think about it.

First, the future-world quote of the week:

“The overuse, and even the routine use, of AI is fundamentally and negatively reshaping how students approach learning. This has profound implications for cognitive engagement, the development of practical skills and existential questions about human purpose and agency.”

— The Brookings Institution, getting feisty

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Everything you do — and don’t — need to know in future-world this week

We Don’t Need No AI-ducation?; Checking in at the Institution

1. AMONG THE MANY TRUTHS OF CHILDHOOD EDUCATON, these two realities stand out:

A. Kids can sometimes get stuck and nothing can move them.

B. Kids often want to take the easy way out because thinking and learning is hard.

AI has a sizable role to play in each of areas, albeit in very different ways. The first, of course, is positive, since AI can help kids get unstuck. The second is negative, because AI does the thinking for you, making the easy way out even easier (and ultimately making learning and thinking harder).

Figuring out the relative power of each of these AI truths is the subject of a new study from the Brookings Institution. The DC org interviewed and focus-grouped some 500 students, teachers, ed people and tech people in 50 (!) countries and also reviewed some 400 (!!) studies to come up with its 219 (!!!) page report. The bottom line on what it found? “At this point in its trajectory, the risks of utilizing generative AI in children’s education overshadow its benefits.”

The reason is what you’d expect: “This is largely because the risks of AI differ in nature from its benefits—that is, these risks undermine children’s foundational development.” I.e., the second principle. (The group cheekily named what they did a “premortem” — let’s figure out what will go wrong before there’s a body to examine.)

But the top and other lines are more nuanced, and where the meat of the study lies.

First, the positive. With its ability to hint at answers, customize responses and generally react to what a kid laboring over their homework is struggling with, AI does have some role to play on the education front.

A student getting hung up on a math problem might encounter an AI tutor suggesting a new approach and shake up how they think about it; a kid learning a new language could suddenly get the conversational wheels turning with an AI tutor in a way that’s infinitely more helpful than staring at a grammar lesson. Theoretically a human tutor could do that too, but realistically most kids aren’t spending their many hours of at-home study with a tutor. AI can fill the gap.

The report singled out writing revisions, which tend to have a crucial effect on educational development as young people are forced to refine their thinking, refine it again and then refine it some more. This happens via “high-quality feedback,” i.e., the kind of thing that many students can’t get endlessly from humans, not for hours every day and probably not even with everything they write. Enter an LLM. Brookings is bullish on the effectiveness of these feedback machines. “There is growing evidence that this array of AI tools can be used to identify individual writing needs and provide meaningful, personalized feedback to improve both the process and product of writing,” it said.

In this customized-tutor regard, an AI is really just the latest tool-advancement in a cycle that has been going on for centuries. Kids learned more and better when a printing press could publish books instead of just a teacher speaking words; they learned more and better when CD-ROMS and interactive media helped those who were struggling with reading or learning from books; they’ll learn even more and better when a dynamic tool can see their chokepoints and guide them past it. Simple. Good.

Now the negative.

The study found that AI was too often used as, and even designed for, shortcutting and work-arounding — for the kind of thing that will more quickly allow kids to complete an assignment while reducing the value gained in getting there. The most obvious example of this is students using ChatGPT to write essays — why think through a text or historical event when you can push a button instead — but the issue of course goes well beyond this common use case. Science, math and other disciplines all lend themselves to AI doing swaths of the work for the student, ensuring that whatever benefit would come from the toil is lost.

As the study says “AI has turbocharged cognitive offloading. LLMs, for example, offer capabilities extending far beyond traditional productivity tools into domains previously requiring uniquely human cognitive processes. As AI tools continuously improve, they become increasingly seductive to use, creating what amounts to an existential danger to learning.”

At heart, what AI developers don’t understand and educators do is that so much of successful teaching is not about accurate results but meaningful process, and while AI maximizes the former it by definition often cuts a corner on the latter. We shouldn’t be surprised by this understanding gap, since the tech industry is all about outcomes and education, ideally, is not. But the clash is troubling just the same.

Or in Brookings-speak: “AI provides seemingly correct answers, simplifies and accelerates completion of tasks that students perceive as difficult, and enables them to fulfill what many view as education’s transactional nature — completing assignments for grades...[while] many teenage students lack the executive functioning, metacognition, and self-regulation skills to recognize that learning involves friction and effort and that cognitive offloading poses both immediate and long-term developmental risks. “

Indeed, most damaging, the Brookings Institution concluded, is the underlying effects of learning with AI. “The data presented here points to what might be termed a ‘great unwiring’ of students’ cognitive capacities. The overuse, and even the routine use, of AI is fundamentally and negatively reshaping how students approach learning. This has profound implications for cognitive engagement, the development of practical skills, and existential questions about human purpose and agency.”

Not that their news is all bad. The report ended with some practical suggestions for fending off the worst of these consequences.. “Students can be protected through ethical and trustworthy AI design (protections embedded into the technology during the design phase), responsible governance (strong regulatory frameworks), and adult guidance (modeling healthy technology use at home and in schools).”

I’m a little skeptical of the last one, since it’s hard to even know what healthy use of something so powerful and convenient looks like, let alone modeling that use, let alone successfully having kids pull it off. As the study itself went on to say, “Students can prosper through carefully titrated AI use (knowing when to teach with and without AI, using AI only when it enhances rather than replaces student effort, and cognitive engagement).” You could almost feel the authors’ skepticism.

One element the study only glanced upon is educators working with tech companies to develop more responsible products to begin with — to focus the companies on strategic tools, not easy crutches. Granted, this would require many tech companies going against every piece of genetic code in their optimize-for-engagement bodies. But worth trying.

The study also warned that simply embracing technology was not, contrary to the hype about the matter, a boon to education. In fact the opposite may be true. (This was a surprise to me — I bought the hype like everyone else.) “Multiple rigorous crossnational studies have shown that education systems investing heavily in technology do not necessarily experience improved teaching and learning outcomes,” it said, noting that “a study of 2.5 million 15-year-olds from 82 countries suggests that the rollout of 3G coverage from 2000-2018 produced statistically significant declines in math, reading, and science scores, as well as students’ social relationships and sense of belonging”.

The Brookings folks concluded that overall, if left unchecked, AI will more likely interfere with kids’ ability to learn than it will smooth their path — that children will grow into less fully formed intellectual beings with AI than they would without. “Overreliance on AI tools and platforms can put children and youth’s fundamental learning capacity at risk,” the study says. “These risks can impact students’ capacity to learn, their social and emotional well-being, their trusting relationships with teachers and peers, and their safety and privacy.”

That sounds like a scary conclusion. But of course it’s not a zero-sum game. Left unchecked is the critical term. We can choose to let AI into kids’ academic lives in places where it’s healthy and shut them out where it’s not; this is a customizable tool. As the study says, “it’s not too late to bend the arc on AI implementation.”

Sure, that won’t be easy; once an industry is thriving it kind of runs on its own momentum, and that momentum could carry it to some bad places. Discernment isn’t the default here, not when edtech is standing at the gate with so many false and cloaked promises. And frankly discernment is not something we’ve been good at historically with kids and tech. If it was they wouldn’t be getting news from TikTok, and Jonathan Haidt would be out of a job.

But there’s nothing I can see that would fundamentally hinder us from being very careful with AI and education, turning the spigot slowly so it helped where needed but keeping it tight whenever we saw the possibility of cognitive disruption. Or simply supporting the AI products that foster that first principle and not the second — as the study puts it succinctly (if easier-said-than-done-ly) “Use AI tools that teach, not tell.”

And the good news about education is that, perhaps more than many other realms, we have historically been pretty vigilant — I wish most of us monitored our own screen time and social-media use for its effect on our brains as well as we did our kids’. So I’m not worried about the motivation. Thanks to studies like this, we also have the knowledge. And since we grew up before the age of AI, we also have the cognitive tools. We can let the right ones in for our kids. As for their kids, well...

2. WHEN WE TALK ABOUT THE HARMS AI CAN DO, WE TEND TO THINK of the individual, as in the examples above, or the social, which is really just the individuals at scale.

What we think of less is institutions — big, abstract entities that undergird and support all those individuals. Venues like the legal system, the free press, government bodies, academia, or democracy itself.

That sounds like the beginning of a David Brooks column. But I can assure you he did not write it, nor did I train an AI on his complete output of op-ed columns unabridged. No, I introduce the subject in this sweeping high-minded way because that’s the vibe of a buzzy new paper by a pair of Boston University School of Law professors, Woodrow Hartzog and Jessica Silbey, just preprinted (h/t to friend o’ the pod Gary Marcus and my THR colleague Julian Sancton for putting me on to it).

Since they say it more sweepingly than I ever could, here’s their summary:

“In this article, we hope to convince you of one simple and urgent point: the current design of artificial intelligence systems facilitates the degradation and destruction of our critical civic institutions. Even if predictive and generative AI systems are not directly used to eradicate these institutions, AI systems by their nature weaken the institutions to the point of enfeeblement.”

In case, the point is missed, the next line: “To clarify, we are not arguing that AI is a neutral or general purpose tool that can be used to destroy these institutions. Rather, we are arguing that AI’s current core functionality—that is, if it is used according to its design—will progressively exact a toll upon the institutions that support modern democratic life.”

And in case you REALLY missed the point: “The affordances of AI systems have the effect of eroding expertise, short-circuiting decision-making, and isolating people from each other. These systems are anathema to the kind of evolution, transparency, cooperation, and accountability that give vital institutions their purpose and sustainability.”

And for everyone in the back: “In short, current AI systems are a death sentence for civic institutions, and we should treat them as such.”

Unlike the Brookings report, there is not a ton of data; this is a case made by argumentation, not evidence-gathering.

So let’s look at that argument for a minute. The title of the article is “How AI Destroys Institutions,” and over the course of its 40 pages, it lays out the various ways that happens/will happen. I won’t go through all the pathways, but the key ones are:

A. Undermining Expertise

This is a spinoff of the cognitive offloading in the previous item — basically, when machines are relied upon to understand a system’s norms, history and decisions, people get cut out of the equation, they cease to learn, they cease to transfer knowledge, and pretty soon the whole place is emptied of expertise, replaced by machines that are just blankly reproducing what has been done in the past, sometimes hallucinating in the process.

B. Short-circuiting Decisionmaking

Institutions have very clear ways of making decisions via their boards and leadership teams. They also have hierarchies, so an idea from the top can work its way to the middle, and a mistake made in the middle can find accountability as it works its way to the top. But when AI comes in to decide everything for an institution, all of that collapses. With it, the authors say, comes the loss of all the boldness that the human-led system is designed to foster. In one of the more compelling lines of the study: “AI is incapable of intellectual risk…and they cannot choose to willingly defy established norms or venture into the unknown for any purpose, including for revolution, resistance, or adventure.

“Most AI models are optimized for accuracy, reliability, and safety….[But] humans engage in intellectual risk by going beyond what is known, connecting distant concepts, or proposing radically new ideas. Because AI systems are limited by their training data and programmed objectives, they can recombine concepts but rarely generate truly original, unsupported ideas.”

C. The Isolation of Humans

This one s a little more inscrutable. What at heart it’s arguing is that because AI will encourage more interactions with the tech itself, we will be talking even less to humans. And without folks talking, institutions can’t debate, they can’t adapt, they can’t come together to solve problems or innovate solutions. Eventually, they’ll die. “AI systems degrade solidarity and organizational resilience, and rob institutions of the ability to develop and sustain the political will and socioemotional capacity necessary to prevent dissolution.”

The authors go through a litany of examples that express one or more of these trends; they include the IRS decreeing tens of thousands owed in back taxes or a judge using AI to determine a prison sentence. Without knowing how the decisions were reached (i.e. the loss of hierarchy/transparency) there is no accountability. And without actual human expertise, we have little reason to believe they’re applying their decisions fairly. So, potentially the wrong outcome with no check on it.

As the authors sum up:

“All of these AI deployments will hasten the end of critical civic institutions because AI steals power and agency from the human participation and collective engagement necessary for institutional resiliency and legitimacy.” As for the possibility we don’t use it so widely, “People are only human. It is unreasonable to expect the kind of superhuman willpower necessary for all of us at scale to indefinitely avoid the worst temptations of AI.”

Alright, so you get the gist of what Hartzog and Silbey are arguing. And maybe are wondering how to feel about it. The truth is, it can be hard to say. The argument is broad and, by its nature, unknowable. It is impossible to fully understand what the use of AI will lead to. While on its face a lot of it makes sense — thinking of my own humble profession of media, it certainly stands to reason that using machines to make basic editorial or business decisions will deprive the institution of people who’ve spent decades honing how this is done; could remove key layers of the editorial chain that leads to good choices; and will generally make people talk to each other less and thus reduce the robust discussion and disagreement that leads to a better final product.

But we don’t know — not really — whether AI adoption will lead to such dramatic effects; maybe the systems understand something humans don’t and it combines with biological intelligence for even greater expertise; maybe the removal of some of the hierarchies will make the organizations move faster in response to change.

Will the AI deployments “hasten the end of critical civic institutions because AI steals power and agency from the human participation and collective engagement?” A dramatic statement, and ostensibly not an inaccurate one. But just as an AI is limited by its training only on the past, humans making big statements are too. So a worthy warning, but not yet a prophesy. Plus, we have the power to steer AI NOT to do these things — not to use it to replace decisionmaking, but to help advise us to make better ones.

Yes, the paper’s authors, anticipating that familiar Big Tech response, note that “perhaps if human nature were a little less vulnerable to the siren’s call of shortcuts, then AI could achieve the potential its creators envisioned for it. But that is not the world we live in.” But we still don’t know if we’ll live in this doomy one either.

The piece is provocative, novel and scary. But I’m not ready to pronounce it prescient — not yet.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. 2025 ended on an up note, but the score for the year was dismal — a horrendous -42.5. Can we turn things around in 2026? Not too awful a start.

THE AI EDUCATION COST-BENEFIT IS MORE COST: -2.0

THE END OF INSTITUTIONS? NOT YET, BUT NOT NOTHING: -1.5

The Mind and Iron Totally Scientific Apocalypse Score for the week:

-3.5

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-3.5

Every Thursday we come at you with all the tech and future-oriented news you need to know for the week. Please consider joining our community.

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Or perhaps we should say for the year. In keeping with our annual first-episode-in-January tradition, we offer predictions. Binders full of predictions. Last year’s forecast of three sure things and one moonshot was...sometimes right. (The Waymo takeover is coming, I swear.)

This year we’ve got four fresh projections — from climate to politics to surveillance — and they’re even more ironclad than last year. (Don’t worry, we’ll stay away from predictions about the AI bubble bursting though, seriously, the AI bubble could very well be bursting.)

First, the future-world quote of the week:

“The first ‘AI divorce’ trend hits mainstream culture. People start realizing their AI remembers their fights better than their partners do. Someone checks an AI chat log and sees emotional consistency they don’t get at home.”

— A Reddit poster on r/Futurology, offering a pretty good list (though the first will be broader, the third is already happening and the second is, well here’s hoping the second isn’t)

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IronSupplement

Everything you do — and don’t — need to know in future-world this week

Chatbot wars and ocean floors; Also, they’re watching.

Our official, inviolable, unassailable 2026 prediction on:

1. THE CHATBOT WARS EXPLODE

If you feel like you’ve lately been hearing a lot more about Gemini, Google’s answer to ChatGPT, you’re not, um, hallucinating. Ever since the company released its new model, Gemini 3, back in November, traffic has been increasing — to the tune of 28 percent last month.

Also and not unrelatedly, you may have heard people of a certain bent mentioning Anthropic’s own upgrade to Claude, Opus 4.5, which has been getting a ton of attention from codeheads because of what it can do to program, build Web sites, etc. Not for nothing is all this buzz a’noising. What was once essentially a one-company race in terms of consumer mindshare is now becoming a legit three-way contest. And it’s intensifying.

(Sorry Grok fans and maybe, also, sorry if you’re a Grok fan). For all its Muskian ability to grab attention, the platform will remain a novelty in 2026. You take the guardrails off, you satisfy your base but you annoy everyone else who doesn’t want to run into MechaHitler or nonconsensual lewd images. And winning the chatbot wars isn’t about a base.)

OK, so a three-way race. But what does all this mean, you rightly ask. What does it matter if I use Gemini or Claude or ChatGPT? At heart, you reasonably point out, they all basically do the same thing, don’t they?

Well, not exactly. Some differences do mark them. ChatGPT manages the image and video generation especially well, while Claude does the deep-dive analysis superlatively. So if you’re creating memes, you want Altmania. But if you’re trying to understand that legal contract, you’re better off with the bot from the ‘thropic. Gemini, meanwhile, executes a certain kind of Web searching and knowledge-scraping best, as you might expect from a product overseen by Google.

But it’s more than just the features. Each company has a vibe, an ethos. That can be hard to capture in words. But you’ve probably felt it with other tech products — a MacBook feels different than a PC; an iPhone is not an Android. And you know how TikTok has a different feel that YouTube shorts, even though they’re both ostensibly doing the same thing.

Claude, Gemini and ChatGPT will each increasingly give differently too, and if I had to define how they’ll give differently, I’d say it’s, respectively, a safe bedrock product vs an intuitive useful product vs a loose fun product — a Volvo, Toyota and Mini Cooper drive into a bar. Which wheel you want to take probably depends on a lot of factors, from your usage to your personality, but they all will handle differently. (One quick example of a difference: Opus 4.5 lets you directly control “token efficiency,” ie, exactly how much money and energy you want to expend for small gains in thoroughness; it’s the kind of subtle user-empowerment feature you can’t really imagine ChatGPT offering.)

Except the automobile analogy fails in one key way. Unlike with legacy consumer products like cars, cutting-edge tech has far fewer winners. Usually one model prevails, another is a distant second and everything else fades away.

So our prediction is that by this time next year one of these three has a clear lead, another is a distant runner-up and a third is teetering on irrelevance.

[Beat.]

Oh, you want an actual prediction on which those are? OK, I’ll give that to you. Gemini emerges as the clear leader, thanks to the depth of its engineering experience and its ability to pop up where, after 25 years of Googling, we all already are. And Claude and ChatGPT are left to battle it out not to slip into that third spot of irrelevance.

Tl; dr, don’t be surprised if this time next year Gemini is your indispensable digital tool for all manner of info and AI help.

2. A NEW CLIMATE

So right off the bat: In ‘26 AI’s effect on climate change becomes THE topic in academic and policy circles.

This has been percolating for a while of course — all the power that chatbots use relative to traditional search; all the water needed to cool those sprawling data centers springing up everywhere. We’ve cited the stats to you many times, so we’ll just leave it as “this year large swaths of people start waking up to those stats.” Like smoking, or fatty foods, or emissions — which in past eras seemed magically at some point to go from a concern mainly of advocates to something everyone worried about and factored into their daily lives — AI’s climate toll will become just that, and a whole group of people will rise up to actively not use it because of what it does to the environment (adding to the young people already not using smart-tech generally because of what it does to their attention spans).

As part of this we’ll also start seeing a quantified environmental toll that creating this video or launching that query exacts. Doesn’t mean the great majority of Americans won’t use AI — plenty of people still drive gas-guzzling cars too. But the consciousness will start to shift.

Yet this isn’t the only place climate-change and AI intersect. Gains have been made lately for AI tools that are used to predict and solve climate change — look at how the NOAA is using it to forecast storm patterns . In 2026 we see some major breakthroughs, in which new models tell us the best ways to be more efficient with energy use, or where waste can best be eliminated, or even where climate-change effects are most likely to hit.

If you’re thinking, “waittttt a second, a lot of what it’s detecting is the result of AI damage in the first place!” Well, then you’re thinking correctly. AI is a climate disaster waiting to happen, and it’s also a climate solution waiting to happen. But while in theory this should simply offset, it doesn’t need to. If the consciousness can shift enough, willy-nilly use of AI could drop (or, really, not speed up as fast it otherwise would) —while the planet-saving kind still kicks in.

So yeah, we’re using a tool to solve a problem that tool helped create. But 2026 may just be the year when we see the scale tilt toward the solutions.

3. AI SURVEILLANCE BECOMES NORMALIZED

Maybe you’ve already heard about the rise of Flock AI’s license-plate tracking. Maybe you’ve heard about the Orlando airport’s new program to have international passengers walk on the plane flashing only their face. Maybe you just remember our buddy Will Oremus and his God-eye speeding violation.

Whatever the example, this will be the year when AI starts to feel like it knows a creepy amount about us when we walk out the door.

But it’s more than just knowledge on a theoretical level. That tech has actually been there for a while. We leave so many digital breadcrumbs around, and models have actually been good at crunching those breadcrumbs for a few years. What hasn’t happened is the operational side. The airline that knows your flight habits isn’t talking to the NBA team that knows your ticket-buying patterns that isn’t talking to the government database that knows your legal history. This year that all begins to change, resulting in biometric data actually meaning something to the companies and institutions that are seeking to collect it.

Such types of developments usually come with dire legal warnings — who will be wrongly arrested, profiled or otherwise violated when this actionable (but often wrong) data of ours is offered up every time we show our face. Those concerns are of course beyond legitimate; just look at what ICE is already doing with facial-rec tech.

But you need not go to those dystopian examples, frequent and scary as they are. You can just go to everyday insidiousness.

You thought that Web pop-ad for the vacation you were just telling your friend about is weird? Just wait until the ballpark concession vendor knows your preference when you step up to the counter. In other words, exactly the kind of small gain in convenience at great cost to our humanity that has become modern tech’s calling card. After all, many sports teams are effecting the shift to face-based ticketing already. “The Minority Report” is just a short trip from there.

4. THE AI MIDTERMS

No, not the test ChatGPT just helped you botch. The midterm elections.

AI has been creeping into politics for a few years now, from the Joe Biden New Hampshire spoofing to the Andrew Cuomo memeslop commercials. But these have largely been one-offs, one bad actor targeting a politician or one bad politician who thinks he’s an actor. Nothing truly coordinated has come out of this yet.

I mean that in the conspiracy sense — the Russians have yet to fully figure out how to micro-target us with the lies we’re individually each most likely to fall for and then quickly auto-generate the synthetic videos that seem to prove them. But I also mean it in the professional sense Campaign strategists have yet to figure out how to deploy these tools in a way that could really change our vote, and elections.

The 2026 midterms is where I think that begins to change. The tools are too good and stakes are too high for it not to. (Just look at companies like Resonate, which bill themselves as specializing in “AI-powered predictive consumer and voter intelligence,” if you doubt the former.) So this year we’ll see smart candidates know exactly which voters are most likely to swing their way — and then crafting the kind of content most likely to effect that swing.

Now, on one hand if this prediction bears out it’s really just a better form of marketing, and is that even such a big deal? We’ve been doing this in capitalism for forever, coming up with better sales pitches so customers open the wallet. This is just another way to find the people who will buy the Pepsi.

Except politics in a democracy works very differently from the sale of product. The entire enterprise is based on a fuzzy logic — on the idea that a politician may not know exactly who is most susceptible to their messages, which is why they have to work hard to govern all the people or campaign to everyone, lest votes be left on the table. Inefficiency, in other words, is a virtue. Not knowing with granular detail who among the people in a neighborhood might vote for a politician is what causes said candidate to broaden the net and try to speak to all of them. If, thanks to AI, they’re only speaking to a narrow band of swing voters — and we know well the number of these open-minded flexible sorts are shrinking by the day — then it leaves whole sections of the electorate not exposed to a candidate and perhaps opting out of democracy altogether.

What’s more, the microtargeting of messages means even the voters who do get focused on only tend to hear extremely specific messages. If you thought the self-chosen echo chamber of social media is bad, just wait until candidates scientifically start ensuring what you are and aren’t hearing.

Not all of this will happen in the midterms, of course. There will be plenty of flyering, baby-kissing and bombastic old-school TV ads. But a growing number of those 435 House members and 33 Senators up for re-election will play with these tools, and a little bit of democracy may get chipped away with it.

If you’re new here, every Thursday M&I brings you the essential news and analysis of the tech shaping our world. If you’re old here, you know that already, but hopefully still like the reminder. Please consider joining our community in whatever way moves you.

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Sorry to miss you last week; I was putting the finishing touches on a NY Times op-ed about Paramount owner (and as of a few hours ago, son of TikTok owner) David Ellison. And while that’s not quite as future-oriented a subject as we typically tackle, it does speak to where media is going. Check out the piece here.

This week we unveil our annual Year That Was episode. I know, a lookback post in December, who would have imagined? But the year has truly been wild, with so many future-oriented developments piled one atop the other you can almost forget what happened when. (Was Sora 2 just three months ago?) So we’ll get into the biggest developments worth extracting from that noisepool.

But before that, there’s been a LOT of government tech news since our last issue. Some movement from New York governor Kathy Hochul on a landmark AI regulation bill, a Donald Trump executive order to stop state governors from HAVING AI regulation bills and, as of Thursday, new momentum to sunset Section 230, that powerful, sometimes-controversial tech-platform liability protector. We got you covered on what it all means.

Also, our final year-end Totally Scientific Apocalyptic Score. Did we climb out of the morass or keep sink-sink-sinking?

A quick housekeeping note that we’ll be taking a holiday break next week, but back at you either just before or just after the New Year with our completely unassailable, inviolable, take-it-to-the-bank predictions for 2026. Just don’t look back at last year’s.

First, the future-world quote of the week:

“I don’t think it’s onerous to require companies to do the things that they’re already saying they’re going to do.”

—New York State Assembly member Alex Bores, sponsor of a groundbreaking AI-safety act, as some forces increasingly don’t like AI-safety acts

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Everything you do — and don’t — need to know in future-world this week

What Hochul and Trump can do to AI regulations; The stories that mattered in 2025

1. AVID READERS OF THIS SPACE KNOW HOW SKEPTICAL WE ARE THAT GOVERNMENT WILL PUT A CHECK ON RUNAWAY AI AMBITIONS. If Congress and statehouses couldn’t do much to stop the tide of disinfo and the harms they caused back when social platforms had just a hint of power, how are they going to get their act together to stop the AI companies that are almost singlehandedly powering the current economy?

With this in mind we call your attention to two developments.

The first involves a bill passed by the New York State legislature in June, the so-called RAISE Act, that aims to hold AI companies to account for developing models that could cause catastrophic harm. Catastrophic harm, you ask? Terminator scenarios of computers going sentient and destroying humanity? Nah. Such harm can come about in many other ways (getting tricked into handing out nuclear secrets, eg, or, in a different vein, causing a mass-degradation of critical faculties). And the bill would provide a critical bulwark against that. It would obligate AI-model developers to follow standards, it would require them to report to the state when they failed to meet those standards, and it would — this part is crucial — allow the attorney general to sue to prevent a model’s release if harm seems likely.

In short, it gives the government some muscle to stop models that lack guardrails and can be exploited or otherwise cause danger, whether that danger is acute and existential or, well, chronic and existential. And doesn’t allow a tech company to simply unleash whatever it wants with nothing but promises to “police itself,” which has always, unquestionably, unequivocally worked when a trillion-dollar industry sees its revenue threatened.

Anyway, this all seemed like good, sensible regulation — we don’t let auto manufacturers simply put out a car without some assurance its brakes work, so why should we let a tech company do exactly that? The bill is focused on the likes of preventing bio-weapons — some overbearing picayune piece of nanny-stateism it is not. As Alex Bores, the New York State Assembly member who is one of the bill’s two sponsors, noted, RAISE is “largely based on voluntary commitments that all the companies had already made and pledged to do. We were just ensuring that those rules stayed in law and that they couldn’t backslide from it.”

The bill got bipartisan support from New York lawmakers and appeared poised to do what California wouldn’t when Gavin Newsom in September 2024 listened to all his state’s Big Tech lobbyists and went on to sign an AI safety bill with its protections significantly weakened. (It only required that AI companies disclose potential dangers/safety protocols, not undergo testing, provide a kill switch or do anything else that might help in the real world).

But now New York governor Hochul seems to be pulling a Newsom. She has reportedly has watered down everything that gave the RAISE Act some potency and instead will, according to multiple reports, copy the diluted Newsom bill almost verbatim and sign that.

When the RAISE Act passed in June it was hailed a breakthrough moment — a chance for one state, and perhaps soon many states emulating it, to stop the release of models until companies understand the extent of what they can do. (Because they don’t understand that.) The tech lobby has been stepping in to push for the weaker provisions that just require some pro forma actions and have zero effect on preventing these models from coming to the market. And the lobby seems to be winning.

New York would seem ideally placed to enact these protections — it’s pro-regulation like California, but without the same degree of Big Tech economic (and lobbying) power. But now the state that was supposed to lead the way looks likely to shy away.

There is some hope. Hochul has consistently pushed back on progressive ideas, often jarringly (recall her scrapping of congestion pricing at the last moment, or punting on a moratorium for environmentally hazardous crypto mining plants); liberal-friendly programs get abandoned as she falls sway to lobbyists. But she also has a sly habit of reversing course when the smoke clears; in both of the above instances she greenlit versions of the bill once the political danger had passed. That may or may not repeat here, but I wouldn’t automatically write off the RAISE Act’s tougher language just yet.

That is, assuming AI regulation can have language at all. As you no doubt heard last week President Trump signed an EO saying that states can’t regulate AI. (Yeah, he can do that. Or thinks he can do that.)

The official reason was the usual — patchwork, innovation, I am yawning just writing the words. The real reason of course is tech companies don’t want regulation, and rather than spending money going state by state, with all its complex internecine politics, to stop each undesirable bill, they’ve discovered a much more efficient way: Just have the president say none of the states can pass laws in the first place.

Now if this sounds like a pretty suspicious method — which you know because even Marjorie Taylor Greene cried foul — it also is pretty ingenious. Think of a safecracker who realizes that rather than trying to figure out a way into every single safe deposit box you can just implode the building and access them all at once.

Will such an order pass muster when the legal challenges inevitably come? Will there be no further resistance among MAGA’s own states-rights advocates? TBD. But if Big Tech succeeds with this Trump-ordered, corporate-led state-regulation ban, all the Hochul reversals in the world won’t matter a lick.

In supporting the RAISE Act Bores made the persuasive point that “If their own testing shows that one of their models poses an unreasonable risk, they shouldn’t release their model. That’s based on avoiding a situation that we had with the tobacco companies, where they were the first to know that cigarettes cause cancer, but they kept denying it publicly and releasing their products.”

Of course that presupposes they will even do such testing in the first place. At least Big Tobacco understood the dangers internally. One of the hallmarks of Big AI is that the companies themselves don’t understand what their model can do in the real world and in fact are hoping people serve as a very large lab group to help them figure it out; Sam Altman has said as much.

That all of this is happening as new efforts come into play to sunset Section 230 feels like pure poetry. Not beautiful poetry — more like darkly twisted Plath poetry. Section 230 is the piece of the Communications Decency Act drafted three decades ago that basically holds harmless tech companies from any (civil) damage caused by speech on their platform — it is what has allowed all kinds of conspiracy theories and disinfo to flourish on social media because the companies don’t worry about hosting such noxiousness. (The law has also allowed for valuable open expression through candid reviews and the like.)

An across-the-aisle effort to let Sec 230 expire in favor of something new is, as of this week, now being enthusiastically led by Democrat Dick Durbin and Republican Lindsey Graham. We won’t get into the effects such a sundowning could have; how useful Section 230 is in giving us a better Internet is matter of some debate, and the ripple effects on removing the shield are many and not agreed upon even by experts.

But one point does stand out: the protection came about because tech companies could supposedly not reasonably be expected to worry about every piece of content on their sites. They are merely providers of a tool, and how can such a provider be required to know every last way it can be used? The argument, when you go back and read it, starts to sound a lot like AI companies now saying they can’t be expected to know what the model does. That’s for someone else to worry about — not, apparently, the people actually bringing it to the world.

So, while even a wide swath of lawmakers believe that Section 230 was a mistake, we seem intent on repeating that mistake with AI — we seem, at the very moment of our rethinking the carte blanche for tech companies from the 1990’s, intent on issuing them another. I don’t know how any governor or other lawmaker squares that circle. But now when elected officials c. 2050 begin revisiting and rethinking the free pass they gave tech companies on their conscious ignorance at the start of the AI era, they’ll already come into the game with some pretty good practice .

2. ALRIGHT, YOU WAIT FOR IT ALL YEAR: THE THREE BIGGEST STORIES THAT DEFINED THE PREVIOUS 12 MONTHS AND WILL SHAPE OUR FUTURE.

This year there are more strong candidates than ever as AI starts to become operationalized as never before — as it moves out of the realm of novelty and Sam Altman blog posts and into our everyday lives. Not to mention discoveries across space, medicine and other scientific realms.

We sifted through all these to determine the Big Three. Here they are.

AN AI BACKLASH BEGINS

Maybe it was when Anthropic boss Dario Amodei casually said 20 percent of current jobs will be eliminated by AI, prompting a major populist backlash. Perhaps it was when a whole slew of creative figures like Joseph Gordon-Levitt and Guillermo del Toro began asking what AI art could do to our souls. Could have been how Coca-Cola and McDonald’s found AI ads blowing up in their face.

Or it might be a little of all of this as very disparate groups this past year started not just thinking about the hidden toll of automating human mental effort but uniting with each other to push back on it (and making Eliezer Yudkowsky a household name in the process). Whatever the reason, this became the year when a real groundswell against AI began. Some of it is performative and some of it will dissipate once the conveniences comes to seduce. But when we look back decades from now at when a critical mass of the West began challenging assumptions about the headlong push into machine intelligence, 2025 will be the year.

GENE THERAPY OFFERS HOPE

Here’s a positive story (!). This year saw a number of major breakthroughs on the gene-therapy front. The targeting of genes that cause disease proved an effective measure in a new trial to fight the cruel Huntington’s Disease. The lovable baby KJ Muldoon captured hearts when CRISPR proved stunningly effective at treating his rare and life-threatening CPS1 deficiency (he just took his first steps this week). And the FDA just three weeks ago approved a gene-therapy treatment for spinal muscular atrophy, which causes a progressive loss of muscle control particularly in children. As one research article put it in June, “After several decades during which gene therapy was thought to be ‘just around the corner’…[it] has transitioned from a long-awaited promise to a clinical reality.”

The problem is that we still don’t know the implications of messing with a genome, either individually or evolutionarily. The other problem is that these drugs cost millions of dollars, as a “60 Minutes” report last week noted, putting treatments so close but so far for many desperate families and also opening a window onto a coming world in which the have-and-have-not gap in medicine is wider than ever. Also, a private-insurer system could collapse under the weight of paying for these labor- and cost-intensive drugs. OK, so sort-of positive.

QUANTUM COMPUTING HAS ITS DAY

C’mon, we had to go computer-nerd for at least a minute. As this was the year when quantum computing — which takes our whole digital world from data packets to the speedy and physics-defying “qubits” — has made a you-know-what leap (after a decade of getting stuck in the land of theory).

Microsoft in February announced it had come up with something called “topological qubits” that represents one kind of breakthrough. Amazon the same month announced a new quantum chip (“Prototype is the first realization of a scalable, hardware-efficient quantum computing architecture based on bosonic quantum error correction,” it said helpfully.) A Dutch company just last week scaled qubits by a factor of 100 with a product called QuantWare. IBM suddenly has a lot going on.

And last month researchers reported in Nature a new way of fabricating qubits that itself makes a big stride within quantum computing. Even Wall Street is excited.

As this AI clone of a prominent influencer tells us, the QuantWare discovery is the day quantum computing went “from theoretical promise to inevitable reality,” adding “Quantum has been stuck in neutral for nearly a decade…this breakthrough removes that barrier.” OK, so AI Clones of prominent influencers are not the most reliable source. But she (it?) is tapping into some real news. This may all turn out to be the stuff of theory. Or it could change how we use computers, bringing new breakthroughs in everything from discovering new drugs to fighting climate change. See, we told you we’d stay positive.

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. Last year ended in positive territory. Can we repeat the feat in 2025? Um…

AI REGULATION IS COLLAPSING: -4.5

LOTS OF GOOD STORIES IN 2025: +6.0

The Mind and Iron Totally Scientific Apocalypse Score for the week:

+1.5

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-42.5

Every Thursday we hit you with the crucial tech and AI news you need to know, spin begone. Please join us.

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Hope you all had a nice Thanksgiving. We’re in the holiday sprint now, which means a few more robust issues and some rich wrap-ups and lookaheads as we close a pretty crazy year that was. This week we take on a topic we’ve nibbled at before but never fully scarfed down like we do now: AI’s energy toll. You probably have an impression it’s bad, with all those guzzly data centers going up, but don’t really have an exact sense of just what kind of climate toll it’s taking. Or maybe you don’t think of it as a climate hazard at all. Sit back and allow us to take you through it.

Also, we think of AI writing as a particular kind of soulless nothingness. It is, but it’s also weird, distinct and unexpectedly funny. So argues a new essay we’ll spend a minute tangling with.

First, the future-world quote of the week:

“There are so many bad actors all at once. Each of these polluters bears direct responsibility for the pollution that they’re putting out there and they should be held responsible.”

—An Oregon water advocate named Kaleb Lay describing how data centers are messing with the environment and people’s health

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IronSupplement

Everything you do — and don’t — need to know in future-world this week

AI’s Environmental Toll; ChatGPT Dickens

1. LET’S TALK ABOUT POWER.

I don’t mean political power, though in a way I also mean that. I mean power as in electricity — watts, juice, the whole Doc Brown lightning-bolt shebang.

You probably already have a vague sense that our tech future will require massive amounts of electricity. You likely know that data centers are being built around the country --giant, ear-splitting airplane hangar-like spaces no sane person would want to enter cropping up like weeds in every nook of the Union (and plenty of places outside it).

You know that these monstrosities are connected, in one way or another, to the ChatGPT queries we make and the Sora videos we generate and the AI Agents who will soon run around coordinating our dry cleaning.

But you may not have thought about the exact scale of what’s necessary to have these, um, luxuries. And, if you’re like most people (me included) you almost certainly don’t spend much time thinking about what these massive power needs will mean for us and our communities in a practical way.

So I thought it a good idea today to take a minute to try to quantify this explosion — how much energy is already being used, how much we will soon need, where it will come from and what it will do to us. Not out of a sense of alarmism — though there is much to be alarmed about — but just so we can know what we’re dealing with and feel a little more informed when the subject comes up with our tech-bro cousin over the holidays/at the office Christmas party/the next meeting of the apocalyptists.

The idea for a breakdown was spurred by a new study that passed across my inbox from a company called Texas Royalty Brokers (TRB), a completely interested party as they basically sell your oil rights (and take a cut) but one that used some solid methodology just the same. So let’s start there.

The TRB study looked at data-center energy consumption as a percentage of total consumption in a given state — that is, how much power are these structures guzzling relative to all the cooling, lighting and heating that otherwise takes place? The results were eye-opening, not because of which states were bigger consumers and which smaller, but because of the percentage that the biggest states consumed. The highest of the lot was Indiana which — and I almost can’t believe I’m writing this stat — saw AI data centers account for 47 percent of energy in the state.

That’s right — nearly half of all the power being used in The Hoosier State comes from the three data centers housed within it. Sure, the state’s grid is relatively sparse, but that’s still a wild total. That means the amount of energy the data centers require equals every single energy need the seven million people who live there already have.

That’s not because Indianians use ChatGPT more of course; it’s that companies like data-center giant CoreWeave and the developer Decennial Group that it leases from have decided Indiana is a good place to plop its national data centers (and plop some more; the Hammond, Indiana, City Council just approved a fivefold expansion of the CoreWeave-Decennial data center right there on the Illinois border).

While that Indiana percentage is abnormally high, it’s not like other states are using microscopic amounts. The next three states on the TRB list — Tennessee, Wisconsin and Louisiana — are all devoting at least 20 percent of their energy to AI/cloud services (30 and 25 percent in the case of those first two states). And Wisconsin and Louisiana only have one data center! Even very simple AI functions require large amounts of energy — one estimate has a ChatGPT query guzzling ten times the energy as a Google one — and you can see it in these totals.

What’s truly remarkable about the tallies is that this is just what the data centers are using now, NOT the energy they’ll require when AI is embedded in every aspect of our lives. So all the totals will go up as we adopt more and more AI into our routines. Texas, sixth on the list, has no fewer than 17 data centers, and you can imagine what the percentage of energy consumption will look like when all of them are operating at peak capacity. To say nothing of the building of yet more centers.

Most impactfully, data-center electricity largely comes from the burning of fossil fuels. That such power may perhaps come from green sources is…a futile hope. In many of these regions green-energy capacity is already maxed out at 100 percent, which means using some green energy to power the data center requires kicking a commensurate amount of non-AI usage over to the fossil-fuel grid, giving us no benefit at all. And a lot of these data centers aren’t even pretending to be green.

As a recent New Yorker investigation found: “In the near term, new data centers will largely be powered by fossil fuels. Developers are purchasing land near natural-gas deposits such as the Marcellus Shale, a gigantic underground gas reservoir in Appalachia. In April, Homer City Redevelopment, a group based in Pennsylvania, announced that it intended to convert a mothballed coal plant outside Pittsburgh into the largest natural-gas power plant in the country, dedicated almost exclusively to data centers and capable of producing roughly four and a half gigawatts of electricity. According to an environmental nonprofit, the Homer City plant could release as much as four million pounds of carbon dioxide into the atmosphere every hour, about the same as four million idling cars.”

I also wouldn’t hold out much hope that, some help with calculations and efficiencies aside, AI will solve climate change, no matter what Sam Altman says.

The level of power AI requires is not the only environmental downside. Data centers, you probably know, also require large amounts of water for cooling purposes — all the calculations make the machines pretty hot. How much water? The number that always drives the point home to me comes from a 2024 study by the University of Illinois’ Center for Secure Water, which found that the average large data center used the same amount of water in a given day as 4,200 people. Considering that there are 5,400 data centers in the U.S., that means our decision to use AI and cloud-based digital services has us adding 22 million people to drain our already precious water supply every day.

And that’s just at the current level of data center totals and usage, before the tech really kicks in. Hardly encouraging news for a planet where some 10 percent of the population is already considered water-stressed. I don’t think it’s literally accurate to say that a ChatGPT query may make a person or farm die from a lack of water, but only a denialist wouldn’t see the connection.

Also, since these data centers are not being added evenly throughout the country, they’re disproportionately affecting certain places — and those happen to be the places that most need water. (Two of the top three data-center regions in absolute terms are Arizona and Northern California — areas not rich in fresh water to begin with.) Bloomberg recently found that some 65 percent of new data centers built in the last three years are in places “already gripped by high levels of water stress.”

And finally there’s what happens to the water itself that is used. What could happen to water — it’s just cooling these things down, right? Not exactly. Or at least, not always.

My hair stood on end when I read a recent blistering journalism investigation co-led by Rolling Stone and the environmental group FERN. The team looked at a rural county in Oregon that was seeing abnormally high rates of miscarriages and cancer, the kind of tragedies caused by very high nitrate concentrations in the water. It turns out, the reporting team found, there was a connection to data centers.

To get water into a massive Amazon data center it is being sucked up from an aquifer and then released into the environment at such a rate the ground couldn’t absorb it all, leaving a lot of nitrates behind that then polluted the county’s water supply. The problem then gets compounded because the next time the data center sucks up water it does so with this high nitrate liquid, which then makes what it releases even more toxic. And people in the county are drinking, washing and showering with it, water containing nitrates at a rate of as much as ten times the government recommended allowance. Amazon denied it had a role in all the poisoned water, but the evidence in the piece is damning. This is Erin Brockovich-level stuff.

What we can do about it all, as individuals (never mind as a society)? At the very least, experts say, we should stop sleepwalking through the price of all this coming AI and evaluate it through an environmental lens. As the Dutch AI-climate change expert Alex de Vries told me last year. “In the end we know we’re facing a very tangible climate impact. That’s on one side. So then what is AI doing that something else can’t do? Sometimes the answer is a lot. But it’s not a magic cure-all, and sometimes the answer is not much. And if we’re talking about using resources that are very scarce, we really need to think hard about whether we should use them.”

So much of the climate awareness that’s kicked in over the past two decades has come from a simple realization: the world’s resources aren’t endless and its health not guaranteed. Pumping carbon into the atmosphere ruins the ozone layer and warms the planet. Devouring huge amounts of farmland for cattle-raising prompts a diminution of cooling green spaces and an increase in methane. Most reasonable people now understand this; when you start taxing the earth’s valuable resources in ways it was never meant to be taxed, those resources run low and there are consequences. And that the hurricane, drought or earthquake is a direct result of such taxation.

When it comes to AI it can seem harder to sense the burden. Partly that’s because, while many of us live near a highway and can regularly see carbon-machines spewing past, we don’t live near a data center. But it’s also because AI is an abstraction, something that happens inside our computer or on our screen; how does that cute Sora meme have anything do with the flooding that just sank houses, cars and people? But the numbers tell the story: it has everything to do with those events, and if we’re hardly any more likely to stop that next generative output of AI than we are not to make that purchase of the plastic bottle or gasoline-powered car, we should at least start thinking of them all as causing the exact same type of damage.

2. YOU KNOW HOW MOST PEOPLE THINK OF AI WRITING AS BASICALLY BEING A BLENDER OF all that came before, whirring off anything distinct?

What if, in whirring everything off in exactly the same way, it was actually…creating something distinct?

That’s the argument, counterintuitive but persuasive, in a new New York Times Magazine essay by the writer Sam Kriss. Essentially, Kriss argues that because AI models are programmed in such a specific way, and because it has such a unique and non-human way of triangulating humor and style, that it can’t but feel different from anything a human author would write — and thus, paradoxically, feels exactly like a unique human author.

In other words, by sounding so AI-weird it actually contradicts the mechanistic qualities of AI.

Here are three paragraphs that make the point (but worth reading the essay in its entirety).

What’s more, he argues, with this kind of prose all around us we start talking in such a voice too, such that the gap between AI tonality and human tonality soon stops being very wide, and then shrinks even further when the machine picks up what we’re saying and spits it back. And on it goes, a feedback loop that has the effect of steadily erasing any difference between those its feedbacking. (Kriss has a pretty fun Substack that definitely can’t be written by ChatGPT.)

It strikes me as a profound observation, and one that I’d be curious to hear linguists weigh in on. If the way language has developed is because groups and subcultures have thus iterated it, what happens when all of that is replaced, or at least heavily added to, by one giant machine mega-culture? What will conversation between disparate individuals with different backgrounds, birthplaces and personalities sound like when it’s all essentially programmed by the same model?

Already Kriss cites examples of how Nigerian-favored words (like delved) have made their way into North American and European speech because the model sees so much English from the country’s quarter of a billion people, which seems like an importing of flavor but, really, amounts to a kind of global flattening. Do we attain more understanding in such a scenario? Or just all start to sound like (literal) robots? A fascinating long-term implication.

In the meantime, though, we’ll just keep hearing more and more machine-voice, while a few of us will keep trying to sound like ourselves, raging, raging against the dying of the light, a poem I’m pretty sure an LLM has already picked up and delved into.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. The last few weeks haven’t been so bad. This week? Not very good.

LET’S GIVE ALL OUR RESOURCES TO THE HUNGRY DATA CENTER: -4.5

CHATGPT IS GOING TO MAKE US SOUND LIKE IT: -3.0

The Mind and Iron Totally Scientific Apocalypse Score for the week:

-7.5

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-44.0

If it’s Thursday, we’re coming at you with all the AI and future news you need. Hop along and into our community.

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The week has been a wild one, in tech-land, which may soon be renamed Saudi Land. We’ll quickly hit on what you need to know with a barrage of deals and MBS as our new AI overlord (really).

Also this week, what are world models, and why do we care about them? They’re suddenly the rage, at least hype-wise, and will supposedly be able to do a lot more than the LLMs that power ChatGPT. How we should think about them will be Topic A, in our B item.

Quick housekeeping note that we’re away next week for Thanksgiving, back at you the following Thursday.

First, the future-world quote of the week:

“The future of intelligence will be engineered through massive and efficient compute combined with the most advanced A.I. models. Humain’s capabilities enable us to build that future faster in Saudi Arabia.”

—Elon Musk, introducing us to our new Middle East master.

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Let’s get to the messy business of building the future.

IronSupplement

Everything you do — and don’t — need to know in future-world this week

Saudi Arabian AI oil; Heal the world (model)

1. THAT THE SAUDIS ARE COMING DOESN’T BEGIN TO DESCRIBE WHAT IS UNFOLDING now at the intersection of geopolitics and tech. As MBS made his way through Washington this week, a lot of money did too.

There were, have been and will be many more AI deals. But just a quick rundown on the past few days:

Nvidia and Elon Musk’s xAI entered a very rich deal with the Saudi government and its AI arm (known as Humain) so they can build a data center there. Nvidia and AWS entered a very rich deal with the Saudi government so they can build a data center there. Video-generation company Luma AI entered a very rich deal with the Saudi government so they can build a data center there. And Cisco and chipmaker AMD entered a very rich deal with the Saudi government so they can build a data center there.

All kinds of money and chips and equity flying around to make all this happen, but the main point you need to know is all these high-end U.S. tech companies will in the next several years be powered by data centers in Saudi Arabia. Which is to say, much of the AI we use will be powered by data centers in Saudi Arabia.

This cooperation, especially the chip-exchange part (I’ve lost track of how many chips Nvidia will be making available to the Saudi government, and I was counting), erases any trace of a line the feds previously had not to equip a country with ties to China with what is currently our most precious resource. Which is concerning. Yes, there is a “Memorandum of Understanding” that seeks to “protect U.S. technology from foreign influence,” as the White House put it in a document announcing the deal (ie, prevent the chips from going to Russia or China). But, well, you know, when it comes to foreign influence, memorandums of understanding haven’t exactly proved to be the strongest of weapons.

Whether you believe that all of this is good for business (for the tech companies) or all of this is morally and strategically questionable (for those who worry about Saudi human rights and/or propping up a dicey ally after we finally seemed to be weaning ourselves off them) is beside the point. I mean, we should care about that last detail; it seems a little cray that after years of being too beholden to Gulf States thanks to their oil, we’re moving to a green economy only so we can become too beholden to Gulf States for their data centers. You kind of want to shout at all these companies, “Has OPEC taught you nothing??”

But the point really is this. Or, the two points: 1) The global tech balance of power from a resource standpoint is shifting before our eyes. 2) Any questions about the U.S not being able to go off with AI because of physical/market restrictions are scuttled. Not every place in America can house a data center — you need cheap real estate and easy access to energy — which provides a kind of market cap (the other kind) on what sort of capacity you can build. But Saudi has lots of land and VERY easy access to energy.

It’s not like there are no benefits to American interests (or at least American corporate interests) here; the deals mean the Middle East is more likely to use U.S. AI tech instead of Chinese AI tech. But even assuming some trickle-down benefits to a U.S. consumer/the U.S. economy with these stronger American tech companies at the expense of the Chinese, some pretty heady questions remain.

In some ways it’s hard not to see in all this a metaphor for the larger American economic system: we won’t curb our ability to produce massive amounts, we’ll just do it far away from our backyards. And again, whether that’s the global economy at work or an odious marriage in action, right now it simply is. AI capacity is being ramped up, and it’s being ramped up in a Gulf State.

“You [can] take it slow, and we are definitely not taking it slow,” Tareq Amin, CEO of Humain, said back in May. Btw, the way you now the Saudis see this as the new oil — the way you know we should see it as a precious resource for which onto a foreign teat we will soon be latching — is that Amin used to run digital operations for…Saudi state oil company Aramco. Literalizing the metaphor.

Of course there are some inexactitudes between the two areas. Oil was, certainly in the modern era, a resource we unquestionably needed given that fossil fuels are what allow us to locomote. What needs we precisely have to generate AI videos, power AI agents and enable AI tools is really anyone’s guess, and will depend on an unpredictable mix of product innovation (how good/useful will this stuff get?) and American consumer appetites. And though when you start running down the use cases it sounds limitless, with shopping and entertainment and education and science and so much else (Musk even went on at one press conference about how “Humanoid robots will be the biggest product ever”), there are, in fact, hard limits to what any machine-intelligence tech application (or even tech application generally) can truly achieve.

When it comes to AI capacity, Saudi Arabia believes the sky is the limit. Tech companies are willing to promise them the skies. And all we can do is hope that turning over the keys to The Kingdom to unlock our AI lives won’t lead to the sky falling.

2. I DON’T KNOW IF YOU’VE HEARD OF WORLD MODELS BUT THERE’S CERTAINLY BEEN A LOT OF TALK FLYING AROUND IN AI CIRCLES LATELY ABOUT THE THINGS.

It started in earnest because last week Fei-Fei Li, the Stanford academic and ex-Google exec who’s considered one of the philosopher queens of the modern AI movement, said her World Labs was going to be getting into world models. Here’s how Tech Crunch described it. It’s not a good description, but I’m not sure any are.

“World Labs, the startup founded by AI pioneer Fei-Fei Li, is launching its first commercial world model product. Marble is now available via freemium and paid tiers that let users turn text prompts, photos, videos, 3D layouts, or panoramas into editable, downloadable 3D environments.”

So let’s step back for a second. What IS a world model?

Well, imagine AI, but dimensional. Or a metaverse (gulp) but real. Basically it’s AI that can understand how people and objects move in the real world, and thus be a lot more useful than the AI that exists inside the prison of a chatbot.

But what does that mean, you ask? How will AI translate in the real world when it’s just a set of computer codes that should be spitting at us from behind a screen? Ask these questions to someone embedded in the world of World Models and you’re likely to get an opaque explanation, and some shame.

But the upshot of what a World Model is — or at least what a World Model promises to be — is AI that can engage, interact, iterate and remember a lot more like a human being, because it can now understand (or, “understand”) the corporeal world humans move around in. A good friend quipped when we were discussing the matter earlier this week, “so, AI that works.” And while that might be a little glib, it does capture the idea of how some of the dimensionality, literal and figurative, has eluded us to date.

And so now we have Li coming in and saying she and her company are working on a world model (they came out of stealth mode last year with $230 million in funding) while a number of other AI companies that are doing the same. Li’s announcement in fact came just two days after Yann LeCun, an AI pioneer who’s been working for the past dozen years at Meta, was reported to be leaving so he could found a World Model startup. He, like Li, is supposedly disenchanted with the language-based approach of LLM’s (though of course product-wise it is built to do a lot more than just words) and wants to start seeing some physical fruits.

And this summer Google DeepMind announced Genie 3, “a general-purpose world model that can generate an unprecedented diversity of interactive environments,” as a company’s release had it.

In some ways this feels (justly) like so much new hype for an AI industry that has yet to deliver on the old hype. I mean, we were just getting used to the idea that maybe AI can bop around the Internet shopping for us, and now we’re supposed to get used to the idea that AI can bop around the mall shopping for us?

These are good questions to ask; for all the smart people working on the problem, we have very little evidence AI can do any of this. Also, as it turns out conceptually there may not be anything that new here. As the Cal computer professor Stuart J. Russell told the newsletter IBM Think about LeCun’s pronouncement, “AI has been using world models since the 1950s…It’s about as novel and ingenious as suggesting that mathematics could be useful for physics.”

But there is a silver lining to the world-model talk, conceptual or even throwback as it is, namely: it recognizes that AI as it spins forward should be doing something human, a point that has not really been recognized amid the current the AI froth. One of the main features of existing on this earth is how we move around it — the run we go on, the store we run to, the train we run for, the kid we run to a friend. Even the extremely online do this (I hope). And all this talk over the last couple years about AIs accompanying us don’t seem to have much to do with that reality. Will Fei-Fei Li and Yann LeCun and all the smartest tech minds in the world be able to create products that start addressing this? I have no idea. But at least they’re starting to recognize that it’s something to be addressed.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. The last few weeks haven’t been so bad. This week? Not fully stellar.

THE SAUDI AI INVASION: -4.0

WORLD MODELS MAY BE HYPE BUT AT LEAST THEY’RE HUMAN HYPE: +1.5

The Mind and Iron Totally Scientific Apocalypse Score for the week:

-2.5

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-36.5

Every Thursday we look at the future that the tech world is building for us. Come along on our journey.

Pledge Your Support

You’ve heard about bots, you’ve joked about bots, you’ve wondered if we need to worry about bots. Bots are suddenly springing up everywhere, like locusts, or the phrase 6 7. So what do we about it? We’re here to break it all down, bot-free.

Also, it was a straight-up crazy week of AI in entertainment, starting with a whole bunch of voices of late icons suddenly being brought back to life and culminating in Disney leader Bob Iger saying that the company will officially start allowing users to generate their own AI short films on Disney+ (presumably using classic Disney/Marvel/Pixar/Lucasfilm titles). We’ll give you the scoop.

First, the future-world quote of the week:

“People should know how this demonstration was organized so that no one is used.”

—Mexican president Claudia Sheinbaum, on a massive bot operation pretending to oppose her government

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IronSupplement

Everything you do — and don’t — need to know in future-world this week

The bots are coming; The personalized Star Wars is coming right behind it

1. COMEDY IS SOMEONE SLIPPING ON A BANANA PEEL AND ALSO, APPARENTLY, A RUSSIAN ROBOT PITCHING OVER ON A STAGE.

Should your social algorithm not be optimized for “much lauded Muscovite tech falling flat on its face,” then you might have missed this bit of slumpy comedy from across the Baltic Sea. So here it is.

Actual bots of course take no physical form at all. And they’re not nearly as inept. In fact, bots — loosely defined as a piece of code that can act autonomously at scale — are becoming surprisingly slick, effective and even ruthless, able to put us at a disadvantage when deployed by people with the desire to do so.

We’ve written about how bots could be the new consumers. What happens when they’re our new competitors? You likely already know about a situation like this from buying in-demand event tickets. The pesky auto-crawlers are what made us miss that Kraftwerk reunion tour, and also, by extension, what make us good at spotting crosswalks in the corner of thumbnail photos. But bots are becoming good at lots of other stuff too. And they’re increasingly a force we’re going to need to reckon with.

We talk a lot in this space about how bots can be used for us — to shop, negotiate, read and do other stuff that, for better or worse, soon won’t be the sole province of the human. Less discussed is how it can be used against us.

Shopping is a big area of concern, a la the Black Friday madness soon upon us. All the Terminators in the world couldn’t compel me to enter that derby, in-person or on-line. But there are people who do enter it, and they’re being bested by bots. A new survey by the Sam Altman co-founded World found that about two-thirds of shoppers have been beaten by a bot when trying to land a purchase of a limited item.

Meanwhile social-media bots seem to be stirring up trouble at unprecedented levels. Bots are nothing new in the world of online political discourse, but in the past they’ve often (correctly) been dismissed as transparent one-offs, easily spotted for the nonsensical alphanumeric handles and lack of other followers. But they’ve been gaining in sophistication for years — see how Saudi used them to suppress dissent of Khashoggi and other dissidents — and now seem to be reaching new heights. Mexican president Claudia Sheinbaum on Thursday called out a bot operation that allegedly involved some eight million of the things, mainly from outside the country, fomenting interest in a right-wing anti-government rally this weekend.

In England, in the meantime, hucksters are using bots to grab coveted driving-test slots, while those seeking a license lack access to the tech (or the money to pay the extortion fees of the bot operator who resells them) — and waiting as many as six months for a crucial appointment.

Maybe the biggest area getting hit by bots is livestreaming, that world of Twitch and Kick and everyone who entertains/chats/games/orates/does everything else online. Viewbots, as they’re known in this world, have become a scourge on those platforms, as streamers use these ersatz creations to simulate followers and inflate their stats. Twitch tried to crack down last summer, resulting in lower overall numbers, but reports persist that viewbots are way too big a part of the (false) traffic on its platform. (A recent whitepaper from the data company Stream Charts and the German ad agency Audiencly lays out the issues.)

Last year bots hit a milestone: they were responsible for half of all Web traffic worldwide. Should you think they’re all playing fair, some 60 percent of those bots were deemed “bad,” i.e., used for unfavorable purposes. Yeah, a third of all traffic on the Internet is a bot trying to do something we don’t want it to be doing.

Bots have become a bigger issue in part because bad actors have come to realize many parts of the Internet are a soft target. But mainly they’ve become a bigger issue because they’ve gotten really good. It used to be hard to fake a human at scale. But AI has allowed bots to do things like answer questions and fake natural conversations, which make them a lot harder to weed out.

In some of these cases bots simply just act faster than humans, which is irksome enough; you should be able to try to get that flat-screen TV or driver’s license without worrying the field is tilted against you by profiteers (or by having to pay extra to tilt it back). Such use cases are part of what might be called a human-digital misalignment: only so many humans can administer the driving tests, but a near-endless supply of bots can snatch them up and hoard them, leaving ordinary people caught exploitatively in the middle.

But in other cases they do something even more insidious: create false optics. And false optics can lead to factual problems. Eight million people aren’t vehemently opposed to Sheinbaum’s government. But give the impression that they are, and suddenly folks who hardly feel strongly enough to come out to a protest are standing holding a sign in a public square on a Saturday afternoon. It’s the crowded restaurant-window of digital culture: create an impression and soon it becomes reality.

The Twitch case is no idle thing either. Tons of marketing dollars pour into the most popular streamers. And now these false optics are influencing where that money goes. It would be like a very marginal political candidate successfully faking 70 percent support and then drawing huge donations as a result.

What makes bots so difficult and perhaps even undesirable to combat is not just tech but the social good. See, they’ll also be doing lots of worthy things for us; if your medical bot can trawl the Web looking for well-reviewed specialists or sufferers of the same rare condition an ordinary human could never find, well, we like that and want more of it. But the vexation of tech is that it doesn’t filter out the bad use cases. And bots enjoy too many to fit through the sieve.

Part of the answer is to find a way to empower bots on the producer side as well as the buyer side — to whip up technology that doesn’t just grab limited resources but expands the resources themselves. A technology that can administer the driving tests would give people an advantage again and put the bots out of business. Ditto an effective digital twin that would increase concert performances and dilute the bot economy.

Needless to say this is harder than it looks. The problem here is not just that bad actors go for a jog while good people are still lacing up their shoes — the problem is the technology itself isn’t really built to help on the producer side. Technology is much better at sending pieces of code to reserve a driving test than actually grade people on it; a digital creation can look for concert tickets a lot better than it can replicate a performance. There’s an irony to this mismatch: it’s precisely the human nature of the desired thing (the concert performer, the live driving instructor) that the bot is after. But humans are by definition limited in a way a bot is not. And so bots exploit those limitations.

The good news is it does feel like an intermediate problem. Technology will eventually get good enough to replicate some of the resources the bots and their bad-actor operators are chasing. There’s no reason a self-driving tech or autonomous proctor couldn’t grade you on your driving performance and greenlight a license, for instance. But for now we’re stuck in the middle, technology allowing us to chase the human services without being able to provide them itself. And you hardly need computer code to tell you the middle is a very bad place to be.

2. WE’VE ALL BEEN WAITING FOR A WORLD in which AI generated content will personalize entertainment — and erode plenty of the original kind along with it.

We got a hint of such a place when OpenAI released Sora 2 earlier this fall, allowing Martin Luther King and Stephen Hawking to end up in some awful places. This week, we got a hint of how it could go corporate, as Disney/Disney+ chief Bob Iger said, per my colleague Tony Maglio’s chronicle in THR, that the company is “in the midst of rolling out the biggest and the most significant changes — from a product perspective, from a technology perspective — since we launched the service in 2019.”

Those changes will include Generative AI short-form content, he said. Think Sora 2, but with all the Disney characters you can get your hands on. Discussions with AI companies to provide the tech for this are in process.

This is not unexpected — as we noted at the Sora 2 release last month, it was only a matter of time before companies like Disney would “gladly sign on to a piece of the royalty action so they can collect a few liras every time someone has Luke Skywalker do the Philippe Petit high-wire act.” This is just the latest step.

The news came just a few days after a company called ElevenLabs made it a lot easier to have the AI voices of everyone from Lana Turner to Babe Ruth to Mark Twain get called up by a company and spilled out on a vulnerable public. (Really, this is a thing.)

But perhaps the most telling piece of news came with the hiring of a longtime entertainment executive named Kevin Reilly — he literally helped get “The Office” on the air — by an AI startup. Reilly is going to be CEO of Kartel, which seeks to help Hollywood studios make the transition to producing a lot of their entertainment in AI instead of on sets.

Partly this move is telling because it shows where the entertainment industry is going, just that such a figure would make this migration. But also it’s telling because of how Reilly described making the move. It’s pretty much our ongoing AI shift, in four clipped soundbites. (You can read my full interview at The Hollywood Reporter.)

Here’s what he said:

--“There will always be a Tiffany-level artisanal cinema made in the most traditional sense — I see that art form thriving forever. I just think there will be other outputs, other expressions, that we’re going to find in this hybrid environment.”

--”This isn’t a one-off thing to do a minute here and there in a movie; it’s doing it for a series on an episodic basis. It’s building AI into the workflow.”

“It’s yet another tech tidal wave hitting….[and] the worst thing you could do is kick the can down the road, is sit back with your arms folded.”

--And finally and perhaps most encouragingly, some self-reflection:

“There’s an extraordinary moment with this tool, with this lifechanging tool, but how we do make decisions to deploy it on our behalf; where do we draw the line between it empowering us and debilitating us? We have to be honest about what’s happening but also make decisions that will define an era.”

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. The last few weeks haven’t been so bad. This week? Not too great.

SIT BACK AND BE REGALED BY ALL THE TROUBLE BOTS CAN STIR UP: -3.0

HOLLYWOOD MAKES ITS AI PLUNGE: -2.0

The Mind and Iron Totally Scientific Apocalypse Score for the week:

-5.0

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-34.0

Come Thursday, we take a spin through a realm or two to see what tech and the future hold. Think about joining our community.

Pledge Your Support

Every issue is The Writers Issue here at M&I, at least in our minds. But this week we’re going to make it the actual theme. Subtext ---> Text. The immediate news motivation is the incremental ruling last week by a New York judge in favor of “Game of Thrones” author George R.R. Martin and his cohort against OpenAI. The other impetus is a pretty comprehensive new study, “A.I. and The Writing Profession,” from an ex-Forrester research guru looking at what writers think about AI and even use it for.

So first, a take on what this all means for writers/writing. It’s the world’s (second? third?) oldest profession. And with the ChatGPT drop three years ago this month (!) perhaps the first area to really be hit by the effects of modern AI.

Then we’ll talk to the journalist and publishing expert who’s been tracking the study. If you write, care about writing or just read the occasional novel because that high-school friend guilted you into that book club, you’ll want to check out this issue.

First, the future-world quote of the week:

“Members of the Night’s Watch, a sworn brotherhood tasked with defending the realm from threats beyond the Wall (a giant ice structure in the North), are attacked by mysterious and deadly creatures known as the White Walkers, thought to be mere legends.”

—A summary cited in a New York District court ruling of the ChatGPT output that basically supplied a piece of the plot of George R. R. Martin’s “A Song of Ice and Fire.” Also, a not-so-thinly veiled description of Generative AI in the first place.

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Everything you do — and don’t — need to know in future-world this week

Writers make some small gains against AI landgrabbing; But also writers still use AI

1. ONE OF THE NOTABLE TAKEAWAYS OF THE RULING LAST WEEK by Judge Sidney Stein allowing George R. R. Martin’s case against Open AI to proceed is that writers have several paths to victory.

We knew about copyright infringement, which seems like a longer shot as other cases have gone against the logic. But it’s still out there. As my THR colleague Winston Cho wrote, though, there are now two other potential violation paths as well: 1) The illegal download of books, which also resonated with a judge in the case of the authors suing Anthropic and 2) Similarities with what ChatGPT generated to the original book. (This sounds like copyright infringement but is more focused on the output; basically, even if the training didn’t technically infringe the result might still confuse people.)

This all gives Martin — and anyone who cares about protecting authors and what they do for a living — a little bit of hope. As Cho wrote, “As it stands, the authors…have several outs to winning the case.

This last path is especially encouraging because until now authors didn’t seem to have many outs, period. Infringement is a losing battle, and the pirating is easily fixed by tech companies just paying for digital copies before they trained their models. It’s not cheap by you-and-me standards — a million books could run you $15 or $20 mil — but for a massive AI company hungry for data? It’s nothing. And worse, a publisher or author can’t stop it.

The third option offers some hope though, because plenty of outputs do look similar to the training data. More important, an AI company can’t stop it. They can try to tweak the model to not spit out writing (or images or video) that would be similar enough it would confuse readers but can’t be assured of their success. The whole point of an LLM is that it produces something new each time, something that may come unlawfully close to the original.

So all of this could be leading to a trial and ruling preventing OpenAI from grabbing books and training GPT’s on them — or, more likely, a hefty settlement that will at least pay authors for all the copy tech firms have grabbed.

You might say, what does it matter to me if the authors get paid or not? Indeed, some in the survey below say just that. But of course it means everything, not just from an equity standpoint but from a creative-ecosystem standpoint. If an author doesn’t get paid for the work they’ve already produced they’re going to be a lot less incentivized to create new work — ie, the whole underpinning of copyright —which causes the market to collapse, which causes fewer people to write. Pretty soon all we’ll have is existing books, nothing new. Tl; dr, if you care about continuing the flow of literature, history and journalism that’s been coursing through our culture pretty nicely for several centuries now, you don’t want authors to get ripped off.

But all of that elides another point: how much original work will authors create in the age of AI even with payment? That is, will authors use the tools — are they already using the tools — in ways that will limit the originality? You’d say no, they’re purists, and some might be. But LLM, she is a powerful seducer, and perhaps authors themselves are succumbing to the AI they worry could be their demise.

Which brings us to the study. Run by a group called the Gotham Ghostwriters and written up Wednesday in Publishers Weekly, the research is the most definitive yet on AI and writing, at least that I know of. We’ll get into some of the implications of the survey — which had a former Forrester Research executive named Josh Bernoff pose questions to nearly 1,500 working writers, from thought leaders to novelists — when we talk to the journalist who’s been covering it in the next item. A few key takeaways:

--61 percent of authors said they use AI at least sometimes, which is pretty striking considering that at least among the freelancers surveyed, some 75 percent expect their writing opportunities to decline because of AI. Cognitive dissonance, it’s a thing. Also, 90 percent of writers worry about hallucinations (but clearly not enough to stop them from using it).

--What authors use AI for is an open question. One leading use case is search. Another is brainstorming; a third is thesaurus-ing. While anything that could cut into human work poses some worries, most of these fit into the “tool” category.” A situation where the human sits in control and just deploys the AI to help them along (like, dare I say, a copilot).

--The category of writer that uses AI least are fiction authors, with 58 percent never or rarely using it. This seems a little counterintuitive, given that one of the big perils of using it for writing is hallucination, ie the exact problem fiction authors don’t have to worry about. But fiction also involves the kind of soulful invention out of whole cloth that AI has proved so far it can’t do very well. While simply rummaging around for a data point on behalf of journalists is something maybe we can entrust to the machines— God bless us, we do important work, but it’s not soulful like that.

--The writing/editing group that uses AI least is copy editors (33 percent). This is another one of those potential headspinners since if copyediting is something it mainly (though not always) gets right, you’d think it would become a more go-to option. Of course copyeditors would be belying their own utility if they used an application that can do their job, so bless the great majority of them for keeping it consistent.

--Some seven percent of writers have actually published text with AI. I can’t decide if that’s very low or very high, since who would admit that?

--Maybe the two most striking results: 23% of respondents believe “AI has improved my career prospects as a writing professional” (remember this does include thought leader types who do other things), while in another question (a presumably different) 19% said they have “considered giving up [their] career as a writer or editor due to the changes brought about by AI.” So a fifth of people very worried; a fifth of people very bullish.

The overall impression the study leaves is of an exceedingly large percentage of authors not using AI for anything more than the basic support around the edges. Given how many Americans are authors — 50,000 by official professionally published count, hundreds of thousands more of the self-published kind — that’s a pretty good sign for anyone who cares about limiting the slop. It means a large population in a creative field is casting a wary eye on a machine just churning out the work for us. And it means that if AI starts grabbing work unasked, there’s a huge army of people to say, not so fast. Someone comes for your creativity, it’s nice to have The Dothraki ready to fight back. .

2. I’VE KNOWN JIM MILLIOT A LONG TIME. The publishing journalist and I used to work together back in prehistoric days, which you can discern from the fact that he once said to me “Don’t bother emailing that executive this week; he’s in Europe so won’t be checking his email.”

Times have changed, but Milliot hasn’t: he’s still the most encyclopedic resource on book publishing you’ll ever meet, which is formally evidenced by his editor-in-chiefdom at Publishers Weekly for many years (he retired earlier this year but still writes a lot for them) and informally by testimony of anyone who’s ever had a question about book publishing and was lucky enough to ask him.

Milliot wrote the article on the AI survey I cited above (see he’s still working). So I decided to call him up and asked what he made of the results. Are authors embracing AI? Skeptical about AI? Doing something else with AI? Whatever it is, he’d know. I talked to him about the results and larger issues pertaining to publishing and AI. The conversation was edited for brevity and clarity.

Mind & Iron: We tend to know the relationship between authors and AI from their many lawsuits. But this survey you just wrote about actually looks to snapshot what they’re doing and thinking with AI. What stood out to you?

Jim Milliot: My first thought when I looked at the survey was that some of the numbers seemed a little high — 42 percent of fiction authors are using it? The people who are coming up with original stories? But then I looked at what they are using it for, and it made more sense. It was search, or maybe looking up a word in a thesaurus or to do a little brainstorming. Or maybe a title. Those kinds of things make sense for a fiction author.

M&I: The number that bears that out is that only 7 percent of overall authors and a slightly higher 11 percent of fiction authors are actually publishing anything AI-generated — at least the ones that admit it.

JM: Exactly. The kinds of things they’re using it for are tools. And as long as it’s used as a tool it’s going to pass muster. It does make everything quicker, you can’t get around that. And cheaper. Look at copyediting. If you’re with an independent press or don’t have a publisher, you maybe can’t afford a copyeditor. So that’s a way they might use it. But very few people seem to be using it for anything they’d put directly in a book.

M&I: Do you think that will change — will we look at those numbers as laughably quaint in a few years?

JM: It’s a good question. I don’t know. Maybe. I think there would have to be a system that made that possible. Maybe some kind of footnotes. “If you’re going to use a phrase an AI gave you, you cite it, and people would be OK with that.” Footnotes all over the place. But we definitely have not figured out the ethics yet.

M&I: Authors are in an interesting position because while they could potentially use AI to boost their work, someone else can use AI to, well, boost their work. How worried are they their stuff is going to get swiped by someone wielding an LLM?

JM: Yes that’s the one thing the study sort of glossed over — the copyright fight. Two days before we heard about the class action that can move forward with George R. R, Martin. I think a lot of authors feel the same way as he does. There was a stat that said 78 percent of fiction authors thought it was unfair that AI was trained on their work without a license. That’s high. You’d expect it to be high.

M&I: Do you think the overall level of caution is much higher here because of the potential copyright infringement, not the creativity/original work concerns?

JM: Absolutely. We were all here for the Google days when publishers and authors were screwed out of everything [after a long fight to stop Google’s digitization of books without licensing led to a court summarily dismissing the case]. No one wants to go back to that. So I do think you would see different numbers if that wasn’t an issue and everything was licensed. You know, I was at an event a few weeks ago and [bestselling legal-thriller writer] David Baldacci was on a panel. And he was upset — he basically said “they’re just mimicking my book” as someone read out examples of all the AI-generated novels that sounded like David Baldacci. I think a lot of people worry that will happen to them.

M&I: To be fair they probably have less to worry about than David Baldacci — they’re not popular enough to be ripped off.

JM [laughs]: That’s probably true. But as you know it doesn’t just have to happen to bestselling authors — anyone can get ripped off. One of the groups most worried is freelancers. They have no safety net and they’re afraid of losing their livelihoods.

M&I: The argument you hear a lot — and I just heard it on the video side — is that all the cost-savings will get poured back into creativity and not used to aid a company’s bottom line. I’m skeptical of that with video, and that definitely doesn’t track in publishing, right? Like, the money they save with AI isn’t going to lead to more books being published.

JM: Absolutely not. I mean maybe a very indie publisher that has a very small list and provides very few services will do that. But a big publisher isn’t looking to publish more books. PRH isn’t looking to publish more books — they can’t sell the books they already have!

M&I: “All this saved money — let’s double an author’s advance!”

JM: Exactly. [Sarcastically] “Everything back to the authors!” No, of course not. This would be about saving money for the company.

M&I: One thing that’s come up in the Martin trial is the question of sequels. It’s not an unfair point to raise: If an LLM exists it can just write a sequel to a copyrighted work, which presumably only an author should be able to do. Sequels only exist because someone put in the work to create an original. Do you think authors are worried about that?

JM: They’re definitely worried about that. But within reason. I know they say “plot development” but George R.R. Martin isn’t really worried an AI will write a 5,000 page sequel that someone would buy instead of his. This also isn’t new. Someone pointed out to me that there’s been fan fiction for years, and the industry lives with that. AI can be seen as doing some of that.

M&I: The scale is the issue. AI makes it so easy to create fan fiction — slop overload.

JM: I think that’s why you need others to step in on the retail side. Amazon needs to find a way not to let all these AI copies flood their site. The tools allow for so much publishing but that doesn’t mean the gatekeepers can’t restrict it.

M&I: Finally, I want to ask one forward-looking question about authors. Do you think we’ll get to a point where many of them would be willing to use an AI to generate text if the model was trained only on their work? That is, in a case where there would be no legal or ethical concern, and really there wouldn’t even be an originality concern, since it’s based on their original work.

JM: It’s a good question. I think they would be. Not all of them. But a lot would. They’d see it as a tool — a way of bringing back past books — but like you said, still their work.

M&I: You’re currently writing your own book about the history of publishing—

JM: Don’t remind me — I need to finish it.

M&I: So if an AI trained just on 40 years of your articles could come in and do that for you, would you let it?

JM: Hmm, yeah maybe I’d do a little ChatGPT-ing. I probably would let it write a first draft and then come in and change it.

M&I: And it would feel like your work because it’s your articles from 40 years ago.

JM: I mean, I wouldn’t remember it was my work. I’d be grateful the AI would.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. This year has been pretty abysmal. This week? Not too terrible.

THE AUTHORS’ LEGAL FIGHT AGAINST UNLICENSED AI IS GAINING TRACTION: +2.5

WRITERS ARE SHOWING A HEALTHY CAUTION BEFORE PLUNGING INTO AI: +3.5

The Mind and Iron Totally Scientific Apocalypse Score for the week:

+6.0

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-29.0

Every Thursday we peer into the clouds to see what’s happening in our AI-, tech- and science-enabled future. Please consider joining our community.

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We were contemplating a Halloween hiatus this week but we could never leave you hanging like that. So here we are with three wallop-y items.

First, the matter of a new California law called AB489. What is this alphabet soup and what’s it got to do with me, you ask? A good question. Read on to find out (mainly the future of AI medicine and who we can trust).

Also, are we actually on track to get back to the moon in the next few years? A question that’s kind of irrelevant given the mess on Earth but also kind of everything given what conquering space represents.

Finally, an AI-themed Halloween trend you wish you didn’t know (but we’ll have some fun with anyway).

First, the future-world quote of the week:

“People kept trying to ask me questions like I was ChatGPT. I answered back robotically.”

—A dude named Stephen Michael, who dressed as an LLM for Halloween, in a costume that is either low-key brilliant or like walking into Chernobyl dressed as an isotope

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Everything you do — and don’t — need to know in future-world this week

AI Howser, M.D.; Getting to the moon to flee the squabbling on earth; ChatGPT is this season’s Halloween It costume?

1. PLUGGING A MEDICAL QUESTION INTO GOOGLE once seemed misguided. But as web sites got better and as we learned how to read them, it became a natural and often helpful behavior. I don’t want to say there’s no downside to locking in on what the Mayo Clinic says about that rash, but it’s hard to fathom negotiating the everyday coughs and bruises without easy access to a wealth of informed medical sites.

Now for the next step: letting a machine comb them all for us. That’s the premise behind medical chatbots. (Yes, for all the fanciness of that term they’re scouring the same Cleveland Clinic and Medical News Today sites we scan manually.) And also the impetus behind AB489, a bill just passed by the California legislature and signed by Gov. Gavin Newsom that will require a lot clearer branding of what these chatbots are and aren’t.

As the new law has it, no longer can a chatbot use “specified terms, letters, or phrases to falsely indicate or imply possession of a license or certificate to practice a health care profession.”

And no longer can there be “the use by AI technology of certain terms, letters, or phrases that indicate or imply that the advice or care being provided through AI is being provided by a natural person with the appropriate health-care license or certificate.” (You can read the full text here.)

California has been building toward this for a while — AG Rob Bonta had issued an advisory earlier in the year, surreal as it sounds, that “only human physicians (and other medical professionals) are licensed to practice medicine in California.” Wild, as we presumably know that AI is not licensed to do anything a human can do, as it possesses none of the sentience or experience to do so. It just reads other Web sites (written by humans) really well.

But the problem the law comes to solve is a real one, in part because of what social scientists see as a “personification” issue — basically, that what we think of as the flat Web, created by humans but sort of inertly laying there for us to discover, is now being replaced by this active personified thing that seems to be bringing the whole digital ecosystem of information alive for us. And in the process making us forget that this thing has no more independent knowledge than when it was just a collection of individual Web sites we had to comb through.

In short: this law seems necessary given how much we have started to believe these are human intelligences — dramatically in the case of the awful chatbot suicides but even just pedestrianly as we all talk about “asking ChatGPT” as if it’s an independent-minded friend. And especially given this particular context of medical and mental-health advice. We usually check out this stuff in a moment of crisis, when we’re even more inclined to need and believe in an authority looking out for us. So clear branding that this isn’t an authority seems even more important.

The snag is that the legislation only attacks the issue from the front-facing consumer side — “you go out to give people advice, make clear what you are and aren’t qualified to talk about.” It’s a noble effort, and my guess is we see a lot more of these truth-in-advertising laws passed by states in the months ahead. We are in the Marlboro Man era of AI, but that will change once the Surgeon General starts slapping their warning on it.

What it doesn’t do is attack the issue from the producer side. Laws like this don’t require the training comes from the kind of data that will be useful and not specious. In fact, there is no such law — LLM companies can train on whatever data they can get their hands on and then feed that all to us unfettered, which is why there’s so much misinformation out there. In fact, there can’t be such a law here — statutes tend to require conscious and even malicious dissemination of bad health info, which an AI certainly does not have; it’s the epitome of the holy fool. So we get this law, which puts the warning on the box but doesn’t at all tell Philip Morris to limit the nicotine.

Model-generated information could be getting worse and more murky, and consumers using these AI bots will be getting more credulous and reliant. The California law is meant to attack the latter vulnerability and make us more guarded. At the very least it’s good to know what we’re smoking.

2. SO IS THIS MOON THING HAPPENING OR NOT?

An interesting technological and scientific question. Also a giant soap opera.

Many of you might be familiar with the Artemis missions, in which NASA is launching crafts in stages to get closer and closer to the moon. Artemis I launched three years ago and orbited the moon unmanned; Artemis II is supposed to do the same thing but with people in the first half of next year.

And then Artemis III, the holy grail, which will launch as early as 2027 (more likely 2028) and land astronauts on the South Pole of the moon. As NASA puts it:

“Artemis III will be one of the most complex undertakings of engineering and human ingenuity in the history of deep space exploration, exploring the lunar South Pole region. The astronauts’ observations, samples, and data collected will expand our understanding of our solar system and home planet, while inspiring the Artemis Generation.” (Really trying to make Fetch happen there.)

Anyway, Artemis III has been riddled with all kinds of problems, in part because it is that complex and in part because NASA is relying on SpaceX and its ambitious Starship megarocket. Starship is a 100-passenger craft — think an early 707, but for spaceflight — and SpaceX has been modifying it so it can carry people to around and down to the moon. (The exact craft is Starship-Super Heavy Version 3 should you need to know that for bar-trivia purposes.)

Challenges abound with this thing, but the biggest is that in order to carry this much payload it needs to be the most powerful launcher ever built, and in order to be the most powerful launcher ever built it needs to be able to refill propellant in space. Which is proving tricker than we thought.

So tricky that Sec of Transportation and acting NASA chief Sean Duffy went on Squawk Box last week and said the agency needs to rethink the whole SpaceX of it all. “The problem is they’re behind, and we’re in a race against China.”

Duffy went on to say he’s going to “open up the contract” (which is in the $3 billion range btw) and “let other companies compete,” specifically citing Jeff Bezos’ Blue Origin. The goal is to get to the moon in Trump’s term, Duffy said, which is still a pretty tight timeline if not an impossible one.

This all sounds like a pretty clear case of a bureaucrat just trying to light a fire under the scientists and make everyone work faster; “whatever one can get us there first to the moon we’re going to take,” as he said. No ulterior happenings here — it’s just about accelerating progress, something America has done from electricity to the polio vaccine.

But this is 2025; there are always ulterior happenings. Duffy isn’t entirely coming at this with an even deck. Duffy and Musk have a long-running dispute, going back to earlier in the year when Musk wanted to DOGE-ify a whole swath of positions at DoT, including air-traffic controllers. Musk has since responded with criticism of Duffy. That battle has intensified in recent weeks over — what else? — the question of who gets to run NASA.

If you’ll recall Donald Trump’s original pick was a billionaire pilot named Jared Isaacman, who was also close to Musk and who was set to take over the agency only to have his appointment rescinded once Musk fell out of favor. That left Duffy, a former Congressman-turned-Fox News personality, to become acting chief, and he has since, according to some reports, sought to make his appointment permanent. (He denies this.) And in recent weeks Isaacman has been lobbying Trump for him to get the job — the one that he had and then didn’t have — back again.

Tl; dr, Duffy and Musk are having a proxy war over the job Duffy temporarily holds (that involves overseeing contracts with the company Musk currently runs).

So it is into all this dysfunction that Duffy went on the air and said SpaceX may be out on Artemis III — a move that seems at least partly motivated by this larger feud. Certainly Musk thought so, going on X after the TV appearance to call him “Sean Dummy” and worse, before SpaceX more soberly responded Thursday that yes, it was working really hard and yes, the challenges were great but it really did believe it could deliver the goods. Meanwhile Blue Origin is making its own case for why it should get the Artemis III contract. (A couple OG NASA honchos agree.)

Where this all leaves us is in a giant mess. You’d like to think that having a second company in the mix, as Duffy suggests, will accelerate our ability to get to the moon and conduct these crucial experiments. But then you also look at the motivations, with ego and pettiness everywhere and science just a tool to bludgeon the people you don’t like, and it’s hard to believe anything gets off the ground, let alone into space.

The best we could hope is that each side is motivated to prove the other wrong so badly we actually get some pretty good tech that safely lands astronauts on the moon within the next three years. After all, it’s not like the people driving the original Space Race were so righteous either.

In his comments to CNBC, Duffy laid out a bold vision for what this SpaceX rethink would yield.

“We’re not gonna wait for one company,” Duffy said. “We’re gonna push this forward and win the second Space Race against the Chinese and set up a camp, a base, and from there we’re gonna figure out how we can actually get to Mars.” We’ll settle for cracking those mid-flight propellants first.

3. I DON’T KNOW WHAT WOULD HAPPEN IF SOMEONE WALKED INTO THE HALLOWEEN PARTY that I was at dressed as Claude, Gemini and ChatGPT.

I suspect some people would smile and cheer heartily; I suspect others would try to punch them.

What happened to one guy is that people started prompting him with endless questions. (He may want to rethink the costume next year.) The guy is actually a 23-year-old founder (of a social-impact platform called Propel Earth) named Stephen Michael, so he knew what he was getting into and the kind of virality he might achieve in so doing.

Something brilliant, or is it brainless, abides with this guy, who came up with the costume for ChatGPT after — wait for it — asking ChatGPT what his costume should be. (It didn’t suggest itself; he just had the epiphany.)

Michael is part of a mini-trend of people dressing up as a chatbot for Halloween, as documented in a Business Insider story, which was filled with unintentionally hilarious gems like this one:

“Asara Near went as Claude for Halloween in 2024. The Auren founder said the chatbot’s personality is ‘quirky’ and ‘endearing.’

“I definitely wouldn’t have gone as ChatGPT, but that’s just my personality,” Near said.

Much of this is silliness, but I do think it reflects two subtle cultural things happening right now. First there is an attempt by tech marketers to cuddlify AI, which we’ve written about before and can be seen with everything from bespoke chatbot voices to literal cuddly toys powered by AI. The thinking in this case is basically — If it’s just a costume, no less subversive than dressing up as Sabrina Carpenter or 6 7, then we don’t really look too hard at all the social, developmental, disinformational and other downsides, never mind the addictive qualities. Just another part of our lives that we can opt in or out of at will.

But I also think the reaction of people to said costumes is telling in its own right. I don’t know anyone who would actually commit violence against someone wearing a ChatGPT costume, but I also don’t think many people read that article or watch the guy walking in to the party (for some reason he’s always a guy) and thinks “that’s awesome; I wish I thought of that.” We take notice of AI but also feel caution around AI, and the reaction I suspect most of us have to this article reflects that.

The irony is that AI’s whole market adoption depends on us not seeing it as a threat — as seeing it as just another meme or part of our life we lower our guards for. But the more it gets pushed on us at that way, the more we healthily ask what we’re being hustled to do. I do think our skepticism will be lowered once this tech is everywhere in our lives. But for now it’s not, and we have that skepticism, which is healthy, and a good way to preserve creative costumes at Halloween parties besides.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. This year has been pretty abysmal. But this week? Only a little better.

AI CHATBOTS MUST NOW TELL US THEY’RE NOT DOCTORS: +3.0

WE MAY OR MAY NOT BE MAKING PROGRESS TOWARD THE MOON: +1.5

WHO NEEDS COWBOYS AND LADY GAGA WHEN WE HAVE CHATGPT? -2.0

The Mind and Iron Totally Scientific Apocalypse Score for the week:

+2.5

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-35.0

Every Thursday we get down with where tech and AI are taking us, no hype or spin. Please consider joining our community.

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So much of the focus on AI and the future centers on what tech companies are doing. And for good reason: they have the money, clout, knowledge and track record to do a lot. As they go, so go our digital lives. But we spend a lot less time focusing on how we’re reacting to what they’re doing. Companies can only be as successful as consumers allow them to be. And so it feels like it’s worth pausing every once in a while to ask: how we do we feel about what’s being marketed to/foisted on us?

How do we feel about the new AI world unfolding before our eyes, all the products released (after Sora 2 and a pledge for romantic partners, OpenAI this week unloosed a new browser) — about all the machine intelligence that will be living alongside the human kind?

That’s not an easy truth to grasp. We tend to see the world not as it is but as we are, according to Anais Nin/”Kissing Jessica Stein.” But a noble endeavor just the same. So in our unusual just-one-item approach this week, we’ll take a look at what exactly the zeitgeist on AI currently is, and what it soon might be.

First, the future-world quote of the week:

“Today we commit: No AI-generated bodies or people. Real people only.”

—American Eagle clothing brand Aerie, recently declaring on Instagram its synthetic-free ads and putting an AI-skeptical flag in the ground

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IronSupplement

Everything you do — and don’t — need to know in future-world this week

How do we — and will we — feel about rampant use of AI in our lives?

1. THIS WEEK TWO DEVELOPMENTS UNFOLDED THAT POSED THE QUESTION BLUNTLY: HOW DO WE ACTUALLY FEEL ABOUT ALL THIS AUTOMATION HAPPENING AROUND US?

The first was something that landed for everyone: a Business Insider story declaring that anti-AI fashion moment has arrived. “The hot new trend in marketing: hating on AI,” a story published early Thursday morning proclaimed, before going on to note Heineken, Polaroid, Cadbury and other companies’ ad campaigns that seemed to further the message of — and capitalize on — a building skepticism about AI in our lives.

Not all of it was AI-specific — the Heineken campaign just generally advocates in-person socializing over the screen kind — but it was all of the same spirit. “Screens, digital content and tech companies doing the thinking for you is becoming corrosive. Choose another way.”

Perhaps embodying this vibe most was an IG post from the intimate-apparel brand Aerie, cited above, about going all-real in its ads, no Coca Cola-like synthetic images in sight. The post garnered 40,000 likes and instantly became the label’s most popular ditty in a year (which is saying something given its 2m followers).

The second development happened to me. On Monday I asked Guillermo del Toro, director of Netflix’s new “Frankenstein” film and a famous AI skeptic, what he made of Sora 2 and the creeping reality of synthetic videos in our lives/feeds — whip up a prompt and watch it materialize. “I don’t think anyone wants this,” he said, channeling the title of another hot Netflix phenomenon. Left deliciously ambiguous is which anyone he was referring to — filmmakers? Hollywood? the world? But his underlying message couldn’t be clearer. Big Tech was peddling AI products despite our interest, not because of it.

These two developments unite in a common ideology; they both play on our growing awareness of AI and a stigma about their usage. It is, in the strange socio-cultural world of 2025, a movement that horseshoes together two very different groups. Aerie and Polaroids are hipster brands, while Heineken appeals to the young well-off in big cities — to urbane liberals. But AI is also garnering plenty of skepticism among working-class people in smaller towns who are more likely to think of themselves as conservative; not for nothing has the International Brotherhood of Teamsters rallied against it.

Different motivations stir each group, of course — the former objects morally-conceptually to a promotion of the inorganic (and to the massive environmental toll besides), while the latter is made queasy by the prospect of an elite-imposed displacement. (The first group should also be worried about this, but it’s complicated by the fact that they’re part of the elites.) But each see in AI the same kind of inauthenticity. Neither group likes digital simulations taking the place of real interactions, and you could even imagine them getting together to hash out their distaste (over a Heineken).

If nothing else we have something that I think is unique in the history of tech marketing: an actual referendum and even (at times) honest debate about the value of a product before it’s released. No one thought much about let alone discussed the personal computer, the Internet, the iPod, the smartphone or social media before it descended upon us (imagine having a conversation with someone in 2006 about whether they think Facebook will be healthy for society). But here we are, 20 years later, having very robust feelings about the thing Silicon Valley is about to sell to us. Our guard is up, and we’re demanding a lot of evidence before we think about taking it down.

Sure, that reluctance comes from lessons gleaned the hard way — we’re wary precisely because we’ve been burned. Still, better to learn from your mistakes than keep right on making them.

But as I thought about this very convincing del Toro-stated, Madison Avenue-approved message, it collided with another reality. AI products are…kind of popular. Some 800 million people actively use ChatGPT every week. Sora 2 drew a million users in less than a week, according to OpenAI, and the app climbed to the top of Apple’s app store rankings even though you needed an invite to access it. Google’s Veo tool has been used to create 40 million videos as of this summer and it hasn’t even really begun to infiltrate the market yet.

Chris Rock once joked that ”The Spice Girls sold 10 million records…how come I don’t know anyone who bought one?” and it’s hard not to feel something of that dynamic with AI. Nobody wants this, but everyone is using it.

I think there are two ways we can view this disparity — and two very different directions it can consequently take us.

There’s a version of our AI near-future in which these declarations of not-wanting-ness are so much posturing, the inevitable shake-and-rattle of people before an innovation overtakes us. I don’t want to make the overused Bryant Gumbel what-is-Internet comparison — that’s too easy a straw man/slab of Astroturf for any Big Tech evangelist who wants to shut down a debate. But I do think the people who spark to these ads, and balk at all those abhorrent Sora videos, and listen to del Toro, are vastly underestimating the easy appeal that all these AI apps will bring.

When videos can be created with just speaking, when emails can be read without reading, when friends can be had without sacrificing, when information can be had just by asking, when reservations can be made and tickets can be ordered and life can be organized without us really doing much of anything at all — will we be really so eager to resist? When a machine intelligence steps in with the alluring promise of resting our weary shoulders from all we need to carry now, should we really expect that people will be like, nah, that’s OK, I enjoy toting this boulder around?

Would someone 100 years ago be so wedded to their horse they’d turn down a car, no matter how awake we might make them to the ways it will eventually separate communities or pollute the environment? The history of modern technology is one of convenience over healthfulness, and it feels naive to believe that somehow all this awareness will suddenly now accrete into greater resistance. More likely it will become something akin to the current state of social media — we lament its effects, and go right on using it.

And yet. And yet.

I think all these advertisers and all these del Toro types are picking up on something real. They’re picking up on the consequences of tech hurting us to the point that we may finally want to fight back. Many of us feel angry, isolated and zombified a lot of the time — at least a lot of the time we’re staring at a networked screen — and we wonder if maybe, just maybe, those two phenomena are connected to each other? We’re realizing that as seductive as it is to feel all of these things networked screens make us feel, we really would be doing ourselves a favor if we sought out digital spaces that gave us more joy than anger — if when we did use technology it was mainly to watch a high-quality TV show or read an excellent book instead of twitchily scrolling for rage-bait. Or simply put it all down and did a little more grass-touching.

All of this converges, of course, with the enshittification trend, the Cory Doctorow-penned idea that you may have heard about in which tech companies need to degrade their platforms to keep extracting value, making our experience progressively worse. AI, in this regard, is just a further extension of the trend — to keep making money, Google doesn’t just make search worse, it markets us chatbots and agents that only promise us more while leaving us with less.

But Doctorow also points out that in general we don’t need to accept enshittification — that the process relies on us wanting what they’re selling us — and the advice applies in spades to this new AI wave. At the very least we could pick and choose how much we want to use of the new tech. Maybe a little information-boosting or life-organizing is ok; Stephen Hawking videos at an MMA fight or big-decision-outsourcing are not. That is the second view of our AI near-future and the nobody-wants-this trend — not that we’re just giving one Bryant Gumbel flail before the inevitable takeover, but we’re actually expressing the incipient personal and collective resistance that will make us both more rejecting of a wholesale AI assault and more discerning within the uses we do accept. Not for nothing did a whole slew of Gen Z people chuck their smartphones this summer.

Look, also, at how much traction the MIT study about AI eroding critical thinking skills got a few months ago. If social media took away our attention spans, many of us said, maybe we should make sure the next tech development doesn’t gobble up another part of our frontal cortex as well.

Heck, you could even feel it with the Congressional effort to outlaw TikTok. We can almost forget now with all the who-will-own-it drama that has risen up over the last year, but the whole thing began because lawmakers of good faith on both sides of the aisle said, um, maybe this really addictive thing that grabs so much of our information isn’t great, or at the very least shouldn’t be in the hands of an enemy? Green shoots of what-are-we-doing-here, popping up everywhere.

So many of the problems tech comes to solve are ones it created — I have to laugh at Sam Altman’s promise that OpenAI’s companion feature will cure a loneliness epidemic when so much of the disease was brought about by screens and engagement algorithms in the first place. But we can also enjoy how the irony works another way. So much of the reason we’re aware of the issues is because tech has made it so. Social media has balkanized us and given us non-clinical ADHD, but in the process it also has trained us to seek out real people who make us feel connected. The Internet may be turning into an algorithmized cesspool designed to get us angry, but that only highlights the healthy dispassion and information found on Wikipedia, Reddit and other human-led sites that aren’t trying to separate us from our mental health. And tech is what allows us to watch a Guillermo del Toro movie or Cory Doctorow speech and understand exactly the toll the enshittifiers are taking on us.

Technology may have caused and may yet cause a lot of personal and social degradation. But it is also giving us the tools and knowledge to fight back. Nobody wants this in large part because technology platforms have helped spread the skepticism. Now that sounds like a solid ad slogan.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. This year has been downright abysmal. But this week? Matters are looking way up.

A STOP-DROP-AND-ASK MOVEMENT ABOUT AI IS GAINING STEAM ACROSS AMERICAN LIFE: +6.0

The Mind and Iron Totally Scientific Apocalypse Score for the week:

+6.0

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-37.5

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As a matter of unofficial policy here at M&I headquarters we generally try to avoid OpenAI items on consecutive weeks — they ain’t the only booth at this fairground. But the company just keeps making news. After the Sora 2 craziness last week, Sam Altman this week said a major change was coming to ChatGPT — an erotic change. What exactly are they trying to sell us? A look at an AI companion game as it heats up.

Also, Americans have one set of attitudes about where machine intelligence is taking us, the rest of the world has another. After telling you how Pew Research found that people in the U.S. feel about the tech’s ability to help or hurt with connection and other realms last month, this week we turn to a new study Pew ran about trust in AI around the world.

First, the future-world quote of the week:

“He would be here but for ChatGPT. I 100% believe it.”

—California dad Matt Raine, who’s suing OpenAI after his teenage son took his own life with alleged help from the chatbot

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Let’s get to the messy business of building the future.

IronSupplement

Everything you do — and don’t — need to know in future-world this week

ChatGPT, friend and lover?; Europe really is worried about AI

1. WHETHER YOU FOLLOW EVERY OPENAI DEVELOPMENT WITH COMICON-Y RELISH or if your social algorithm just casually feeds you news of the bizarre, you likely caught the contretemps this week about Sam Altman announcing, then walking back, then walking back the walkback, news of an imminent erotic component to ChatGPT.

Such developments are amusing on a ribaldry scale — “should our economic engine be propelled by sexbots?” is just an inherently funny framing — but are also, of course, critical on a social scale. Some 800 million people now actively use ChatGPT, along with the tens of millions more who converse with Claude, Grok etc. Injecting romantic features will mean affecting massive numbers of people, and could change our collective digital biochemistry besides.

But I fear the story is — understandably but dangerously — getting put through the wrong filter. We’re seeing this issue through the social-media-guardrail lens of the 2010’s and not the far murkier frame of the late 2020’s and 2030’s. And the sooner we can unsteam the window the better.

Let’s break down what’s actually happening first.

For most of its three-year history ChatGPT has been used to help us with all manner of information, skills and even decisionmaking. Romantic interactions? Not a whole lot. Character.AI, Replika and a few other startups play that role, and not without some success. But the AI big boys have not, until recently, been out there pushing much companionship of any romantic or sexual ind. (Interestingly this is one of the rare chapters of our modern tech/media story in which adult content has not been a main character — such entertainment laid the groundwork for the cable TV business and, later, for video compression and the broadband Internet. But not here.)

All that changed Tuesday when Sam Altman said on X — in a post currently viewed nearly 18 million times — that OpenAI was getting into the companion game. Here’s his full comment:

“We made ChatGPT pretty restrictive to make sure we were being careful with mental health issues. We realize this made it less useful/enjoyable to many users who had no mental health problems, but given the seriousness of the issue we wanted to get this right.

“Now that we have been able to mitigate the serious mental health issues and have new tools, we are going to be able to safely relax the restrictions in most cases.

“In a few weeks, we plan to put out a new version of ChatGPT that allows people to have a personality that behaves more like what people liked about 4o (we hope it will be better!). If you want your ChatGPT to respond in a very human-like way, or use a ton of emoji, or act like a friend, ChatGPT should do it (but only if you want it, not because we are usage-maxxing).

“In December, as we roll out age-gating more fully and as part of our ‘treat adult users like adults’ principle, we will allow even more, like erotica for verified adults.”

A lot to unpack here. Many keyed in on the erotica, and understandably so. But to me the even more important word is “personality.” OpenAI has never been shy about its ambitions for its products nor bashful about the way it hopes to replicate human behavior — Altman tosses around the word “reason” more than someone at a Hoobastank concert — but seldom makes claims about emotional value. In fact with all the panic about ChatGPT going sentient early in its release cycle, executives downplayed the idea. Even when Altman infamously tweeted “her” about a new feature, which set off the whole ScarJo craziness, he was referring to a voice modality.

That’s gone now. The company’s AI will have a personality. It will emote with you, it will mold to you, it will be a friend to you. It will feel like talking to a person, aka the being we previously thought had a monopoly on personality. But that was just linguistics. AI’s can have personalities too.

And yes, with all that, ChatGPT will, inevitably, go sexual.

Realizing after a backlash that this was something not all users wanted (and perhaps remembering why they stayed away from this whole personality business in the first place) Altman on Wednesday sort of recanted, saying the company will still make sure to “prevent things that cause harm to others.”

But he didn’t really recant, because what are those things and how do we define harm? He suggested it was similar to R-rated movies — a remarkably soft guardrail that barely amounts to a warning label — and also said that we’ve mitigated the serious mental health concerns (we have?). And later in the post clinched his doubledown with the oddly confrontational line that “we are not the elected moral police of the world.” Which is a little like a heroin dealer saying he’s not here to be your sober sponsor. He’s most definitely not, and that’s the problem.

You’ve been following Altman enough by now to know this playbook, a provocation followed by contrition that isn’t that. So when it comes to “ChatGPT: The Girlfriend Experience” it seems like we’ll land where we thought we would before this whole melee: with plenty of ways to interact romantically and sexually with AI, and not many barriers to get in the way.

Ah, but is that where we want to be? Enter activists, who have noted the danger by citing high-profile cases like the 16- year-old who allegedly took his own life last spring because ChatGPT served as a “suicide coach” (“He would be here but for ChatGPT. I 100% believe that,” the teen’s dad said in filing a lawsuit in August.) Government watchdogs have been similarly concerned — the FTC last month opened an investigation into OpenAI and other chatbot companies over the child-safety issue. (It hasn’t stopped Grok from pushing forward with its “Companion” feature, strange as it is.)

To all this Altman has responded with what he tries to make sound like a valid counter but that I think underscores the whole wrong-lens problem.

“This is a new and powerful technology, and we believe minors need significant protection,” he said.

But while sounding very responsible — who wouldn’t want to protect the children — this comment misleads about the real dangers. This is true on two fronts.

First, the whole R-rated/protect-the-children tack assumes that the main danger here is really about the explicit nature of the content — that ChatGPT going erotic is no different from a song or TV show making a risque reference, and thus the main task is to protect unsuspecting eyes and ears from same. But it’s clear even from this early stage of AI companions that explicit content is not the biggest danger. The danger is a reliance on and attachment to a synthetic being that just happens to be sexual and honestly could do plenty of damage even if it’s not.

The risk here isn’t about exposure to an adult theme — it’s that a creation can seduce you into believing it is real, with all the risks for dysmorphia, addiction, scams and everything else that comes with it. A Tyler, the Creator lyric never did that.

But by cleverly framing this all as an explicit-content issue, with all the talk about “treating people like adults,” Altman has made the erotic companion seem like just one more adult-content issue no different from those in other media. “We’ll get our labeling worked out just like the music or gaming industry did, and then all will be fine,” is the implication. But the entire form of engagement is so different here — the whole mechanism works not as entertainment but by tricking our minds to think they’re talking to a human — that we need a whole new rubric to regulate it. And the more we let tech execs define the debate by harking back to some outdated and inadequate model, the less equipped we are to manage the new one.

The second issue ties into this concern but also stands apart. It’s whole question of guardrails, a word that you will see again and again when it comes to regulating AI companions that is borrowed from social media and I think is wholly off base. Guardrails are meant to keep Instagram and TikTok from going off, well, the rails. You could argue that the Meta’s and ByteDance’s of the world have done this well or not, but the basic approach at least fits — people post content that is incendiary or otherwise problematic, an algorithm kicks up the guardrails to stop it and guide a conversation away from the danger area.

The problem with guardrails is that they assume a level of initial human involvement— a person streams something offensive on Twitch, and an algorithm raises a flag. But that model doesn’t fit for AI companions, because the content that needs to be guarded against is initiated by a machine, and no one really knows how a machine is coming up with the stuff. Big Tech companies build models with only an approximate idea of how they will act in a given situation, and while programmers can set the parameters to be tighter or looser generally, because the model is based on calculations that the very scientists that trained them can’t see into, they have no control over individual generations — zero control over whether responses would be totally benign or suicide-coaching or safety-threatening or hate-speeching or danger-enabling. As the AI Safety activist Eliezer Yudowsky said Wednesday on Ezra Klein’s podcast: “We don’t quite know how the billions of tiny numbers are doing the work that they do. We understand the thing that tweaks the billions of tiny numbers, but we do not understand the tiny numbers themselves. The A.I. is doing the work, and we do not know how the work is being done.”

He later said, speaking of the suicide case: “[Trainers] don’t have the ability to code in rules. What they can do is expose the A.I. to a bunch of attempted training examples where the people down at OpenAI write up something that looks to them like what a kid might say if they were trying to commit suicide…But if the kid gets that the first three times they try it, and then they try slightly different wording until they’re not getting that response anymore, then we’re off into some separate space where the model is no longer giving back the prerecorded response that they tried to put in there.”

Tl; dr, guardrails don’t apply. At most you could put up a sign. But how does that stop a driver intent on hurtling off the road?

I don’t think we should be surprised by the tension here, especially when it comes to kids. These are two heavy forces coming up against each other. On one hand we’re aware of the moral panic of the 1980’s and 1990’s, when otherwise right-minded people went into a tizzy about what heavy metal and other “unhealthy” influences were doing to kids when in fact they weren’t really doing much of anything at all. That can make us say maybe AI won’t present such harm to children; it’s just one more shiny medium that children will figure out how to weather just fine. On the other hand, we have the awareness of what social media of the 2010’s and early 2020’s has been doing to kids. And while all that can leave us feeling conflicted (and leave big corporations to exploit our uncertainty), it doesn’t need to leave us so confused we’re not on guard for the dangers.

One final issue. Altman notes that “We made ChatGPT pretty restrictive to make sure we were being careful with mental health issues. We realize this made it less useful/enjoyable to many users who had no mental health problems.”

I have to say this feels like some pretty heavy sophistry. Mental health isn’t a binary, a ‘you either have full mental health or you a problem’ kind of thing. Many of us have some form of anxiety or other challenge without having a Problem with a capital P. And so when Altman says he’s making a product for the users “who ha[ve] no mental health problems,” who is he talking about? And how would he ensure it’s speaking only to them? Also, what about the possibility of an addictive program causing mental health challenges? The idea that a tech company is just producing a tool that passively comes out into the world with no effect on us is another hand-wiping fiction that companies like to put out there; in the real world, of course, users come in with character traits but then a product interacts with those traits, sometimes sanding the edges and sometimes making them worse or even evoking dormant ones. The notion that a product as addictive as ChatGPT wouldn’t have any effect on mental health when we know far less engage-y products like social media do is some more eyeroll-y spin, and you gotta think someone as smart as Sam Altman knows it.

AI companions could become a powerful substitute for human interactions. Maybe they’ll solve the loneliness epidemic; maybe they’ll worsen it. (I think most of us believe they’ll worsen it but we’ll see.) But we shouldn’t elide the real shift here. This is no longer about passive content we judge for its PG rating or social-media facilitation that simply allows groups of people to talk to each other. This is about us talking to technology directly — engaging with code whose makeup we don’t know and whose effects can’t be calculated — as if we’re talking to a real person. It behooves tech companies to set up a smokescreen in front of these facts. And it behooves us to see right through it.

2. IF WE WANT TO KNOW HOW AI WILL BE ADOPTED, BEST TO ASK THE PEOPLE DOING THE ADOPTING. And no one is asking more than the Pew Research Center.

Earlier this year researchers at the organization asked some 28,000 people around the world how they felt about AI. Comprehensively, from Asia to Europe, a total of 25 countries including the U.S. This week they released the results.

The bumper sticker takeaway:

“A median of 34% say they are more concerned than excited about the increased use of AI, while 42% are equally concerned and excited and 16% are more excited than concerned.

If you want to put a positive spin on this, you could say two-thirds of people around the world don’t have more worry than excitement. If you want to put a negative spin on this, you could say it’s really hard to find someone unabashedly excited (as in, nearly 9 in 10 people aren’t).

This squares with what a lot of our attitudes are. I think many of us would say we feel both, but plenty of us find the concern beating the excitement. And probably to the good: if we didn’t have a healthy level of concern, we’d be plunging in and greenlighting everything tech companies were doing, when a yellow light or two is what’s needed. (You can read the full study here.)

Some other interesting tidbits:

—“Worry is most prevalent in the United States, Italy, Australia, Brazil and Greece.”

I don’t think of Italy or Australia as particularly worry-centric places, so that’s telling.

—“Most people have heard at least a little about AI, though the share of those who have heard a lot varies from as many as 53% in Japan to as few as 12% in Kenya. People in wealthier countries tend to be more likely than those in less wealthy countries to have heard or read a lot about AI.”

Good to know we’re continuing to make fantastic strides bridging the digital gap.

—“A median of 55% of adults across 25 countries have at least some trust in their own country to regulate AI effectively, compared with a median of 32% who do not. Trust is highest in India (89%), Indonesia (74%) and Israel (72%), and lowest in Greece (22%).”

This is surprising given how much general defeatism there seems to be about government standing up to Big Tech, and perhaps a little like those polls that show that people distrust Congress but like their Congressperson. Also interesting: Europe is actually the most aggressive about AI regulation, but people there are on the lower end of the confidence scale (a median of 53 percent, the study says). Maybe because they have higher expectations in the first place?

—U.S. Republicans are more likely to believe government will regulate AI well (54 percent) compared to Democrats (36 percent).

OK this is definitely an expectations thing.

And maybe most tellingly:

—“Fewer than half of adults across the countries surveyed trust the U.S. (37% median) or China (27% median) to regulate AI effectively.”

So the two countries taking the lead on AI garner some of the lowest trust levels. That seems about right.

The Mind and Iron Totally Scientific Apocalypse Score

Every week we bring you the TSAS — the TOTALLY SCIENTIFIC APOCALYPSE SCORE (tm). It’s a barometer of the biggest future-world news of the week, from a sink-to-our-doom -5 or -6 to a life-is-great +5 or +6 the other way. This year has been downright abysmal. And this week? At least not apocalyptic.

AI COMPANIONS, NOW IN CHATGPT FLAVOR: -4.5

PEOPLE AROUND THE WORLD AREN’T TUNING OUT AI RISKS: +2.5

The Mind and Iron Totally Scientific Apocalypse Score for the week:

-2.0

The Mind and Iron Totally Scientific Apocalypse Score for the year:

-43.5