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A busy week, culturally and legally, when it comes to AI.

First, since we last met I saw a new movie that I think could legitimately do more to change perceptions about AI than 100 articles (/Substacks) combined. Read on for more.

And the big news this week: Eight attorneys general sued OpenAI for what they allege is major harm that ChatGPT is causing users, including and especially teenagers. This just after OpenAI released a report saying it’s all chill, and a nonprofit said not so fast. How dangerous is ChatGPT for young people? We investigate.

First the future-world quote of the week:

“OpenAI, they wanted to be the first to market. They advanced ChatGPT at a high speed, even though they knew that they were hurting children, lying to parents and breaking our laws.”

—Iowa attorney general Brenna Bird, commenting on why she and the AGs from seven other states are going after the company

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

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

The states get even; Garfield hates Sam-day

1. YOU LIKELY CAUGHT THE NEWS THIS WEEK THAT EIGHT STATES HAVE SUED OPENAI FOR what they say are harms caused by ChatGPT.

The company engaged in “willful, dangerous, reckless and unlawful conduct” with regard to children, who in many cases forestalled getting the actual mental-health help they need and in some cases even hurt themselves,” per the lawsuit

The actions from the eight states — from not-exactly liberal litigation-mongers like Iowa, Kansas, Montana and Arizona — follow a June suit from Florida (ditto) against OpenAI for allegedly causing a “litany of harms” like addiction and abetting suicides. Chatbots’ day of reckoning in court is coming, a lot faster than Meta’s did back in August for Insta and Facebook after 15+ years of harm — and possibly with penalties much greater than that company’s $18 billion settlement.

Given how the legal proceedings are now going in these childhood-harm tech lawsuits — don’t forget the Meta and YouTube judgments in the “KGM” trial earlier this year — I’m optimistic that many of this new wave of AI suits will go the prosecutors’ way, or at least the momentum will be strong enough to force a decently substantial settlement. The question is whether it will change anything in how these companies operate. In an ideal world, such stiff penalties force structural changes simply through deterrence — who wants to get dragged in for one hefty settlement after another? And so AI companies completely disallow anyone under 18 from using their product, or let mental-health experts vet their training data and install guardrails, or do any of a number of things that would make a difference.

The problem is that for companies with valuations at these levels the penalties aren’t actually all that hefty, and executives may take a calculated gamble that not upsetting the Wall Street apple-cart with all these limitations on users is more important than paying a fine or four later on.

Which means the actual goal of the suit or at least the goal most of us care about — structural remedies — won’t be achieved in the courtroom the way we might have hoped. At best we’ll get some minor changes (August’s Meta settlement requires some night-time blocks and the like — nice but hardly the kind of thing that will stop addiction, more just make the drug dealer a little less accessible. The real solution to AI harms will have to be legislative, and we’ve seen almost nothing regulatory as yet on the federal level and only scattershot efforts on the state one.

Meanwhile, the urgency grows and the data mounts. The AG lawsuits follow closely other developments on the teen-chatbot front. OpenAI came out with a report last week that said “less than 2% of teens spend more than three consecutive hours on ChatGPT.” Which was quickly countered by a Common Sense Media report that the company’s teen-specific ChatGPT product alerted parents too late when their kids brought up suicide and self-harm, and seldom suggested help itself. The latter study is a lot more credible, and its main thrust goes unaddressed by OpenAI’s own accounting. Plus the company’s claim doesn’t even seem persuasive on its own — “consecutive” is doing a lot of work in that sentence. So two hours before dinner and two hours after dinner is chill?

The argument that defenders make on behalf of ChatGPT — that OpenAI makes on behalf of itself — is that plenty of humans can encourage harm and foster delusions in young people too, just as plenty of (hopefully more) humans can promote well-being and give them a healthy sense of self. Yet we’re not banning all humans from interacting with young people, they say. So why would we stop ChatGPT? The “it’s just a tool” point, basically.

What this argument misses, of course, is that, well, for one thing we don’t allow human adults to run around unsupervised with children either. We vet Tommy’s parents for whether their boy is worthy of a playdate; we put trust in schools that the basketball coach, drama teacher or guidance counselor can have a good influence on our children (or do some added investigating ourselves). No such inquiry attends our use of ChatGPT, in large part because we CAN’T vet a model this way. A system like ChatGPT is meant to be dynamic, drawing from endless reserves of training data and generating responses based on a user’s input. It’s like a babysitter that keeps firing and replacing itself with a whole new babysitter. How can a parent, short of spending every minute of every day with their kid, know what ChatGPT will do? It doesn’t even know what it will do.

That should mean a lot more wariness for a chatbot than a passive streaming show. Yet when it comes to chatbots we tend to exhibit less. We check that kids are watching age-appropriate material or even put controls on their profiles. But far fewer safeguards exist for a bot that, unlike a pre-written script, can literally go anywhere.

OpenAI’s answer has basically been in the “trust us bro” vein — “we encourage breaks,” “ChatGPT is just there for support,” “it’s meant to be a helpful learning tool.” (I was struck by the line in the OpenAI study that usage figures for ChatGPT “reflect a different kind of experience [than social]: ChatGPT is designed for learning, building, and creativity, rather than passive scrolling.”

Well, it may not be passive, but I’m not sure how you can ensure the first three, and if a kid is having mental-health challenges it seems that the responses from a bot are at best a roll of the dice on whether it will say something neutral and at worst a legit risk for making a bad situation more awful — in either event, not a vehicle for creativity and building.

All kinds of other squishiness hovered over OpenAI’s report, including the line “On average, teens spend under 15 minutes a day on ChatGPT.” Averages are quite useless in a realm when some 40% of kids don’t use it all and thus naturally drag an average down, while the people who use it thus do spend a lot more time than 15 minutes per day. The better metric would have been the median amount of time, but that data point is nowhere to be found. Also, 2% of teenagers is still half a million kids in the U.S., and putting that many young people’s fates in the hands of something so unknown and unknowable for that many hours is hardly the “only” situation a statement like this is meant to imply.

As Iowa AG Brenna Bird said, “OpenAI, they wanted to be the first to market. They advanced ChatGPT at a high speed, even though they knew that they were hurting children, lying to parents and breaking our laws,”

The whole thing reminds me of football and CTE. You may recall that a lot of fuss was made about the scale of head injuries about a decade ago — consumers becoming aware of the dangers of the product they are cheering on with their pocketbook if not actively seeding with their kids. The NFL did much of what OpenAI is now doing — release a series of helpful-seeming but cherrypicked and ultimately obfuscatory reports, make some half-hearted tweaks, and hope that’s the end of it.

Can we do better? The lawsuits and public outcry are a start. But we should make sure to press on. Because it’s worth remembering where we ended up with football — everyone moved right along with only a marginal reduction in risk. And the NFL’s ratings are higher than ever.

2. “ALL THE PRESIDENT’S MEN” AFFECTED how we see journalism, “Kramer vs. Kramer” affected how we see divorce, “The Hurt Locker” affected how we see war and “Chariots of Fire” affected how we see people running in slow motion on the beach. I think “Artificial” can do the same for how we see AI — the movie could literally be the kind of cultural turning point we’re still recalling decades after the fact.

Nominally an odd-couple bromance that becomes a frenemy (or really just enemy) story between Sam Altman and former chief science officer Ilya Sutskever, Luca Guadagnino’s film, with Andrew Garfield as an increasingly powerful and off the chain Altman, soon becomes a stand-in for everything we’re dealing with now, not just on AI but tech in general.

I wrote about “Artificial’s” many-splendored vibes for THR here. (And we of course covered the real-life drama between Altman and Sutskever in M&I that crazy November 2023 weekend here.) But I wanted to raise two points about how the Christmas 2026 film achieves its goals — why I think it lands such a shot to the solar plexus and will have such an enduring effect.

First: The best way to show a villain may be to not make them villainous at all. That’s not to say Garfield’s portrayal doesn’t make you want to hurl a shoe at the screen — the utter contempt for his own employees (trying to save him from himself) will have you grabbing for your Nikes. But for much of the film he’s a charming and winning dude — occasionally a little fast-and-loose with basic safety considerations, sure, but hardly the purveyor of evil that AI Safety advocates like to portray. You may not choose him as your best man, but you certainly think he knows how to responsibly steward a company.

Only when his small acts of duplicity and sabotage start creeping in do we realize the extent of the pathology, and only when he starts flouting major safety concerns do we realize the cost that pathology could come with.

This mirrors how Altman’s public image played out, a sort of gradually-then-suddenly arc. But leave the fidelity aside. This choice works dramatically, and I suspect the alarm bells the film sounds will thus ring that much louder. Dangers that sneak up are much more chilling than dangers shouted down.

Second: the subject of the film. You might think that AI Safety warnings should be about the sky falling. Indeed a lot of AI Safety warnings are about the sky is falling, and if you ask most people what comes to mind when they hear about “AI dangers,” some Terminator-type scenario comes to mind. Of course the problem is that conveying it this way loses its impact over time — we’ve seen too many stories of autonomous machines taking over to feel their effects, like a tooth shot through with too much Novocain, and besides, going so big with the warnings just allows Big Tech companies to wave aside all concerns as hysterical.

“Artificial,” on the other hand, lands its message precisely because it’s not engaging in any far-off scenarios — in fact it’s not engaging in any scenarios at all. No constructed scenes here of AI escaping control or falling into the hands of bad actors. (Though Jason Schwartzman has a pretty good moment as an ex-techie, now bearded and bedraggled, laying out to Sutskever the awful possibilities.)

No, “Artificial” is simply trying to show a man, Sutskever, losing control of what he created. And that loss of control is so potent but more to the point so relatable that it does the work right there. You don’t need to watch an AI hacking into a water system or electrical grid to understand why accelerationism is a bad idea. All you need to see is the man with good intentions who wants to stop it get run over by someone not much concerned with it. Then your mind fills in the rest. (That Amazon dropped the film, leaving an indie/non-tech-affiliated company to pick it up, only adds paint to this palette.)

There will be some people who paint “Artificial” as a corporate-executive drama, and in one sense of course it is. But I think that undersells what’s really happening and how it will work on us. The executives in question aren’t just fighting for their share of the pie: they’re engaged in a battle royale between profit and responsibility. And the movie’s clear victory for the former may well just make those of us watching it more energized to protect the latter.

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? We had an up-and-down summer. But the fall is looking solid. This week, more of the same.

LOT OF VERY REPUBLICAN STATES GOING AFTER CHATGPT: They just need to bring on structural changes: +2.5

A NEW MOVIE COULD FINALLY LAND THE MESSAGE OF AI SAFETY: +4.0

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

+6.5

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

+8.0 (!)

Every Thursday, we got the future-world news for you. Hop on for the vibes.

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This week we thought we’d take a break from all the AI Safety madness — hey it’s worth a shot — to strike a bit more of a philosophical note, exploring not so much what technology is up to but why we engage with it in the first place. A bit of a stepback, as it were, on what we’re doing here. So scroll down for a piece that asks all of us to look at our relationship with technology over the decades — and whether the one we have now is the best one we’ve ever had (and want going forward).

But also, OK, in this same week as the AI leaders met with Donald Trump and agreed to all that “tremendous self-regulation”, we did want to weigh in a * little* bit. But who needs a column? A picture is worth a thousand words, and an “SNL” sketch is worth a thousand pictures. They aired an AI one last weekend, and a better commentary on the state of affairs (/delusion) I cannot imagine.

Li’l housekeeping note that after some nonstop action this past month we’ll be off next week for a Columbus Weekend break, back at you the Thursday following with all the forward-looking news your heart desires.

First, the future-world quote of the week:

“We do not condone what we are doing.”

—Dario Amodei, as imagined by “SNL’s” Jane Wickline

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

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

Lorne leads the way; Got a blue turntable and a microphone

1. LIKE ALL GOOD SKETCHES, THIS ONE IS SO SIMPLE IN ITS PREMISE and yet so... layered in its meaning. It consists of nothing more than Dario Amodei, unable to stop himself from saying the quiet part out loud (literally). And yet every time you hear an AI CEO warn that what they’re doing is really dangerous, just think of this bit and somehow all the contradictions and self-serving paradoxes will become clear.

2. THIS PAST SUMMER I TOOK A VACATION TO A LAKESIDE CABIN IN THE MIDWEST. Rustic would be an overstatement; this joint was monastic the way Thoreau popping over from Walden Pond to have dinner at Mom’s was monastic.

Still, even among the well-appointed furniture and modern kitchen appliances, something about the experience felt stripped down. Perhaps nothing embodied this better than a device resting on a little stand in the den: a Bluetooth turntable. That is, a regular turntable, but made for the modern age, and thus equipped with a Bluetooth connection. You still could only listen to one record at a time, one song at a time, with all the pop-and-hissing, all the needle-dropping, all the you-gotta-get-up-and-flip-the-record-if-you-want-to-hear-more-songs-ing. Except with said Bluetooth connection, you could beam it easily to speakers set up at sweet spots around the room.

Now, you may well have a rig like this in your home; if you don’t you can easily imagine the appeal. On this trip I wanted to take advantage of the pleasure newly afforded me. The owner of the Airbnb had a pretty solid vinyl collection, and so as I went about my vacation I would regularly rock out to vintage Beatles and Dylan and Denver and Stones and Winwood right there in the Minnesota hinterland.

The experience was perfect. The music and the vinyl may have been old-school, but the sound wasn’t — thanks to the Bluetooth speakers I could easily adjust how I listened and how clearly it came through. Perfect.

This little moment of musical bliss — of unplugging, sleekly, with the help of this setup — got me thinking about how we use technology, what we want from technology. And it cast me back — way back, to the times not long after the turntable first dominated. Let’s take a spin.

If you grew up in the middle part of the 20^th century, you began to get a sense that tech could offer a pleasant boost, the calculator and the clock radio and the automatic transmission all making life just a little bit easier. You suddenly didn’t need to learn how to shift gears or add really big numbers; technology could just do it for you. (I’m defining technology here as commercialized science for populist use cases. Obviously there are many definitions.)

If you were grew up in the last 25 years of the 20th century, you felt this acutely too, during the time of the Walkman and VCR and the first personal computers, all making your life a little bit easier. Suddenly could make mistakes on that term paper and quickly write over them, or leave your house and not miss any television, or leave your house and bring your favorite music with you.

This continued into the early part of the 2000’s when Google and the iPod and the Blackberry came on the scene. You could now move your email out of the house with you too, and the entirety of your music collection instead of just a few CDs, and that whole Encyclopedia Britannica to boot. The improvement over the previous era was noticeable, but it was primarily one of volume, not substance.

But sometime around the late 2000’s this shifted. You could peg the change to the introduction of the smartphone, or the advent of Facebook, or the interaction between the two, or to factors larger than both of these. But something got a little more complicated at this moment — something that we’d never really witnessed through the entire modern development of technology. Suddenly, for the first time, we didn’t just have a quantitative shift — we had a qualitative one.

Because now what was being sold to us was not a product to make our life easier — not a tool that we could wield as we liked. Suddenly something very different was being sold to us: ourselves. Suddenly, the tech companies were treating us like the product instead of them manufacturing products and selling them to us. Suddenly we weren’t being sold anything at all.

We were giving something, something more important than money — our sanity, our social interactions, our time, our sense of calm. All in exchange for...what exactly? Sure, in the moment we could give it definition — a chance to connect with people we never met, or read news articles (and later watch videos) we never would have consumed, or some other barter we could muster up a reason for. But really, if most of us were asked what we were getting for all we gave, we probably couldn’t offer a very good answer. The modern, social, algorithmic world just kind of happened. And pretty soon we just accepted it as our reality.

I can’t emphasize this point enough, because it embodies the whole era we’ve just lived through and really will undergird the era of AI. Tech companies used to leave us in charge and make money by appealing to our sovereign impulses to buy this product or sign up for that service. But that type of business is laborious and unpredictable for a large corporate enterprise looking to make profit at scale — I mean, selling someone a new product each time out involves a lot of front-end costs and a lot of back-end uncertainty. Better to hook someone, better to “engage them,” using all they already gave you to enable this to happen.

And so we have dating apps that keep us just hopeful enough but don’t give us exactly what we want so we stay subscribed (and, at times, upsold) forever; and so we have social sites that know how to give us just enough info to feel provoked and wanting and coming back for more, often compulsively, dozens of times per day; and so we have viral videos or mobile gaming or Kalshi-betting that addresses an itch that never quite feels scratched; and so we have streaming services that put that next great binge just around the corner. When a company has the level of microdata about what makes us click and what makes us stay, this is not hard to program to — especially since one side knows how to do the hooking and the other side, at least until recently, didn’t realize it was being hooked.

A lot of us now say we’d like to go back to an era before this happened, but I don’t think we fully mean it; would you really want to wait a half hour for that car service to call you back while standing on that rainy street corner or wondering where the nearest restaurant might be with no way of finding out? We like the convenience the constant plug-in gets us. What we mean, I believe, is that we want all those conveniences without the exchange that seemed to happen when we got them —without the rage-baiting, without the data farming, with the noise-cluttering.

(If you want a cool take on this de-individualization from someone who was way ahead of the curve on it, check out Jaron Lanier’s talk launching off his seminal 2010 book on the subject, “You Are Not a Gadget.”)

Anyway, you don’t need to squint too hard to see how AI will make all this much worse, not only because it makes the data that much easier to collect and the selling that much easier to automate, but because AI itself will become the product — that is, we’ll be so reliant on this intelligent-seeming being for our therapy, our companionship, our decisionmaking, our life tasks, we will completely give in to the pivot, the tech fully controlling us instead of the other way around.

The era of social algorithms preserved at least the illusion of sovereignty — we signed up for that platform; we can theoretically quit it anytime we like. But the AI age will strike away even this facade and make us very visibly reliant on another sovereign — on the bot that will take on that negotiation (Muse is already doing this); on an agent that will go out and vet the first date (as I was just telling someone, Hinge 2.0 is not the algorithm passively sorting matches but actively going out to meet other AI Agents and reporting back whether someone is worth meeting — such admirable efficiency!); on another intelligence that will process all kinds of information for us and then act on it before we even get a chance to.

Ah, but for every Big Tech action there is an equal and opposite reaction. At least there might be given our dawning awareness. This stripping away of the facade of sovereignty won’t be nearly as simple as it once was — we won’t all be reflexively signing up for Muse in 2027 the way we were for Facebook in 2007. Or if we do, we’ll be asking more questions, demanding more control, approaching the whole thing with a warier eye.

I’m not so naive as to think that a tech backlash will be overwhelming or massively neutralizing. Nor do I necessarily think it should be. Innovation is an engine often driving us to the good. I get a small frisson of hope at the thought of a person sitting alone who would never go to a therapist now having an AI mental-health agent to talk to. I enjoy knowing that AI can keep my elderly aunt company or teach that smart-but-struggling kid the stuff the school system has long let slip through the cracks. Let some of this stuff in.

But also, let the right stuff in. Let stuff in with a critical gaze. We missed the distinction between consumer and seller — we missed the realization that we should be the purchaser not the product — once before. I don’t think we should or will be so quick to miss it again.

We’re already seeing little shoots of this. One easy example is the so-called “flip-phone” movement — the trend of teenagers and college kids hurling their smartphones into the sea and instead using their flip phones to communicate. That means social posting is largely out and doomscrolling is way out, but they can still find ways to meet up with friends and not get stranded. Also, photos and texting can still happen. (Here’s one of the new models meant to cater to this movement.)

An odd and even precious gesture on the youth’s part, you might say. But I think it only looks that way because the modern tech economy is not built for the kind of life this growing group is seeking. These young people want technological utilitarianism — they want to use the product without becoming the product — and they’re making that preference known by buying such phones (I mean, they wouldn’t be made if there wasn’t a market). By letting Big Tech know that, if they’re a square peg in a round hole, maybe Silicon Valley should start putting in a few more right angles. As the unboxer in the video above says, “Although the slowness discourages you from using the phone, that’s kind of the whole point.”

They’re making their preference known, really, that what they want is the Bluetooth Turntable — a return to a world where tech is used, no doubt, but to enhance something analogue and human, not to replace it, or us. Where the balance of power shifts away from the addictiveness to the intentionality.

They’ll hear the Beatles and Winwood and the Stones, and with pristine sound, but on their conscious terms, not on the terms of an algorithm that has farmed their preferences, whipped up some recommendations, and tried every button-pushing, brain-deconstructing trick in sight to keep them listening (and paying). They’re hearing the music thanks to technology new (beaming the sound wirelessly across the room) and old (let’s face it, does even the best chatbot compare to the idea of someone putting grooves in a piece of vinyl, spinning it really fast and eliciting the most beautiful sounds known to man?)

We’re far from knowing where all these AI products will take us and how we’ll react to them, individually or collectively. But I think we might want to approach this unknown new place with a little less of a headlong rush and a bit more of this standard of Bluetooth Turntablism. That is, with a willingness to embrace anything that can enhance our listening experience — but always ensuring we’re the ones putting on the record.

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? We had an up-and-down summer. But the fall is looking solid.

SNL COMPLETELY SKEWERS THE ANTHROPICRISY: +3.0

TOWARDS A NEW TURNTABLISM: +4.5

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

+7.5

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

+1.5

Every Thursday we bring you the crucial stuff on a future bearing down. Please join us.

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After a few weeks of AI Safety, we’re going back to more eclectic programming. Not because the safety issue has been resolved — as we type this Australia reports a rogue OpenAI agent went after its Medicare service — but because we all need a break from the doom.

So we’ll tell you about something a little more hopeful. Well, eventually hopeful: Tech that can reduce the need for animal testing.

Also, Mark Zuckerberg says it’s great, but should we use Muse? We’ve got what you need to know.

First, the future-world quote of the week:

“I had to trust Muse with my most personal data, which included connecting it to my bank accounts and email. Two weeks in, I found Muse to be the most useful A.I. app I had ever used.”

—The NY Times’ Eli Tan, going big-if-true

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

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

Muse Plugs in, Baby; AI Saving Animals

1. NEARLY FIVE YEARS AGO, MARK ZUCKERBERG UNVEILED HIS VISION OF THE METAVERSE, AN ANNOUNCEMENT THAT LACKED IN SUBSTANCE WHAT IT COMPENSATED FOR WITH HYPE.

Needless to say, the idea didn’t take off, give or take a pair of glasses. And though I wouldn’t rule out various forms of virtual living in the next decade — in fact, I’d bet on it — Zuckerberg’s idea of an all-consuming 3D reality in which we play out our social days isn’t happening anytime soon.

Yet as with so much of life — and certainly tech life — what had seemed like an afterthought soon became the main event. No one gave much thought to the notion of AI Assistants back in the fall of 2021 — ChatGPT itself was more than a year away. And yet here we are in the fall of 2026 with Muse, Zuckerberg’s newly released AI Agent, starting to look like a real player.

Unlike the metaverse, he’s actually first this time, with no other public-facing consumer agent yet available despite everyone and their grandmother promising they would be. OpenAI has tried, then walked it back. Sure, people ask Gemini questions and yes, Claude edits that document or codes that app. But as we’ve been noting for a while, an AI Agent does far more, and more proactively, in handling all the sundries of life; it both remembers the birthday and orders the gift. Among many other tasks we now wait on hold or go online to do.

The consumer reviews on Muse have been trickling in. We’re not the product-testing sort here at M&I, though we’ll try it out soon enough. We do like to see how something is going over and stress test some of those assessments. And no piece is as worth a prod as Eli Tan’s firsthand account in The New York Times this week.

After choosing his “wren” avatar and getting to work, Tan makes no bones about what he thinks Muse is capable of — “I Gave My Life Over to Meta’s A.I. Agent and Was Blown Away,” reads the headline. He indeed gave over that life — and bank account and other personal information — and had Wren deal with everything from haggling with antique vendors to working out dental-insurance payments to summarizing podcasts.

As Tan writes, “I had to trust Muse with my most personal data, which included connecting it to my bank accounts and email. Then I had it perform dozens of day-to-day tasks, including ordering my groceries, scheduling my meetings and setting my fantasy football lineups. Two weeks in, I found Muse to be the most useful A.I. app I had ever used.”

All sounds pretty good (except for the fantasy team; what self-respecting manager would entrust a machine with a task that important?). There he is, downloading eagerly and handing over happily. And Tan is hardly alone — the agent sits atop Apple’s rankings of most-downloaded apps.

The author writes of Muse’s convenience appeal. “Very quickly, I found that Wren could efficiently fill out online forms, a tedious part of using the internet. I could take a photo of a parking ticket, and Wren would pay it for me, asking for approval before making the payment.”

It also achieved the holy grail of any digital assistant — it spotted an accounting error.

“One clarifying moment came after I connected my credit cards to Muse and asked it to track my spending in Google Sheets. I watched as it spun up tabs with hundreds of rows of data each in minutes, then flagged two duplicate subscriptions, which it canceled for me. Then Muse used my email to request a refund for a free newspaper trial that had expired, saving me $44.99.”

Meta is good at nothing if not a cozy interface, and the idea of the avatar sitting in a little on-screen circle and studiously banging away at the laptop, as Tan’s chosen “wren” can be seen doing, provides heaps of concretizing reassurances to those users wondering what exactly an agent is doing and how it’s doing it (never mind that the idea of a cute digital bird pecking away and ordering your groceries is as ridiculous a representation as your car’s dash would be if it showed a little man sitting inside the engine pedaling with his feet). When it comes to new adoption, anthropomorphism is king, and none rule like Zuckerberg.

There are obstacles: Amazon is currently blocking Muse. They say it’s data-security but come on, they don’t want anything coming between them and the consumer. So for the moment you can’t dispatch it to shop for you on the world’s biggest retailer. That won’t last though; Amazon just needs a minute to figure out how to mine your AI Agent, which ultimately will be easier and more fruitful for its algorithms than mining a human since all that annoying unpredictability will be removed. It’s always easier for an algorithm to know another algorithm.

So exciting has all this been that Zuckerberg took the stage at Connect and said that, well, “In the coming years, I expect that Muse is going to grow into the personal superintelligence that billions of people around the world are going to use to accomplish their goals and improve their lives.”

Alright slow your roll there Mark; this isn’t the nonexistent Metaverse. Paying Con Ed isn’t the same as making us complete human beings. Still, the bill-paying isn’t nothing. One has to give credit to Muse for doing the things most of us don’t like doing. We may have, at last, finally entered the AI Agent era.

And while Meta is no stranger to hyped releases that simmer down — remember when Threads was going to take over the world? — I can’t help feeling like we really have turned the corner. Whatever ziggy line emerges from here, we probably won’t ever fully go back to the days when AI Assistants fail to autonomously, with only occasional programming updates or check-ins from us, handle a lot of the humdrummery of daily living.

Tan does conclude, after he finished personally talking to a ceramics seller he wished to buy from, that he preferred that interaction. “Sometimes people just don’t want to have their personal lives automated, even if the technology is good enough,” he wrote. You think? Of course that seller will have their own agent soon enough, so I’m not so sure there’ll really be a choice. One unintended consequence, though — the ease with which we’ll soon deal with these kinds of tasks, and the companies dispatching their own agents, may incentivize everyone to increase the bureaucracy. You know, the info-collecting, the surveying, the identifying. Call it induced-demand theory of AI Agents — make chores more frictionless, increase the chores.

Personally I don’t feel comfortable enough with the level of security the current crop of agents offers , and I don’t think the amount of time one would save me from dealing with these chores and customer-service tasks would be worth the risk, especially considering you’re going to have to go back and check the work anyway. (For Tan Muse weirdly couldn’t do something as basic as ordering baseball tickets.)

But I, unlike most, prefer to do something myself even when others are offering it to do it for me; I’m the rare American who wouldn’t want an assistant, should my good bosses at THR ever think me worthy of one. Of course many people are not like me, and they do like an assistant, and for them the prospect of occasionally getting something wrong is a small price to pay for not constantly needing to worry about getting it right. So for all of those folks, yes, use Muse — let it order your gifts, deal with your insurance company and summarize your podcasts.

Just give over your data sparingly and with some redundancy; if you give it a bank account number, make sure your life savings isn’t in it. Be prepared for some mistakes and frustrations — it wouldn’t surprise me if we soon start hearing about someone using an AI agent to, say, initiate a breakup...only to find it accidentally proposing.

But embrace the massive wave of convenience Meta’s Muse brings. And think of all the ways to use your newfound free time. Hopefully not by scrolling Instagram.

2. I WAS LUCKY ENOUGH THIS WEEK TO ATTEND A SCREENING OF “THE NEW GOLD STANDARD,” a documentary about the tech that’s replacing animal testing made by the filmmaker Steven Latham.

Animal testing is one of the great travesties of our time. More than 42,000 dogs, 12,000 cats, 57,000 pigs and 107,000 monkeys are tested on each year in the United States alone, often in ways that are not only cruel and inhumane but also actually useless for science. Pointless product tests from vestigial bureaucracies that leave animals hurt, scared and euthanized for no reason. Or endless medical tests like we’re living in the 1950’s when the science indicates there’s little benefit. Often the animals chosen are those most docile — the number of beagles tortured every year for no good reason is heartbreaking to consider.

The reason this happens, the film shows, isn’t science but money: pure, cold money, for everyone from breeders to third-party testers to transport companies making lots of cash on a system that benefits no human, just their own pocket, and in return inflicts unimaginable pain and suffering on innocent animals.

But a movement is looking to change this — a movement coming from the scientific community. A whole raft of experts, people from leading medical institutions and universities, all showing that, ethical concerns aside, there’s actually better science when we use what’s known as human-relevant data. (“Significantly cheaper, quicker and more predictive,” as Latham said at the screening.) And so a whole lot of startups and VCs are starting to foment this change. (There’s also an amazing place called Kindness Ranch that rescues these animals; they’re deeply worth checking out.)

More on the particulars of these tech startups in a future issue, but a quick namecheck of Emulate and Hesperos, two biotech firms that basically put the information and actual cells of an organ on a chip and lets researchers experiment that way. Or the research by former American Heart Association president and Stanfordite Joseph Wu, who is creating human “organoids” — basically mini-organs grown from stem cells that accurately model the real thing. So if you’re testing a new heart or cancer drug, you can do it on the human organ itself, and not a poor monkey or pig that won’t really tell you much anyway.

Not to mention a whole bunch of companies doing AI modeling — computer simulations to indicate how drugs will interact with the human body. All of this will make for more effective drugs that reach a market quicker.

“There’s a whole effort to keep the status quo and pretend human-relevant science isn’t ready for primetime,” Latham said at the screening, referring to the entrenched interests trying to stop these new companies from gaining a foothold. “This film’s goal is to kick those doors down.”

Congress this summer passed the FDA Modernization Act 3.0. It forces/institutionalizes the changes more loosely announced in a 2022 bill to move us beyond animal-testing requirements for the organization (the biggest tester in the country) and allow dogs to begin leaving research facilities, among other changes. The NIH, meanwhile, has ORIVA, an office that looks at human-centric solutions to what were previously animal-testing ones. We are heading, slowly, to a less animal-testing future and, even more important, to a future where the tests actually tell us something about how the drugs will work on humans.

There are many questionable use cases of AI and biotech. But this one is all good — better testing, less cruelty. Our tech future isn’t always about removing the human — sometimes it’s just about making us better ones.

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? We had an up-and-down summer. But the fall is looking solid.

MUSE COULD BE USEFUL, IF NOT ALL-OUT INSPIRING: +2.0

BIOTECH SAVING US FROM ANIMAL CRUELTY: +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:

-6.0

Every Thursday we bring you the essentials on our tech-y future. Please join our mission.

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We’re keeping it super-short this week because I’ve been at the Toronto Film Festival for THR covering the craziness over the Elon Musk documentary, which international distributor Universal Pictures is seriously considering not releasing even as some voices internally push executives to hold their ground. If you’re a regular reader of this space you know the warnings we’ve sounded about giant corporations gatekeeping journalism — a particular problem when Big Tech interests enter the picture — so no need for me to repeat them here. Suffice to say that Gibney’s movie is exactly the kind of rigorous questioning of power structures that we need. One can only hope that all of his corporate partners do the right thing.

But for our purposes today, the AI Safety debate. With OpenAI’s Hugging Face attacks and Anthropic’s Jacob Coxon whistleblowing, we told you last week about the bombshell developments, This week, the blast zone expanded, as politicians, tech leaders and your grandmother’s gardener all weighed in. So we’ll spotlight three of the most salient developments before curling into a ball of blessed sleep.

First, the future-world quote of the week:

“We have plenty of laws. We have plenty of regulations that govern the reliability and the functionality of products.”

—Nvidia chief Jensen Huang, assuring us AI barons have everything under control

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

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

The Three Bares

1. THE RISE OF TRUST ME, BRO-ISM. OK, so it’s not like it ever sank. Tech executives for the past 30 years have been saying they’ve got the whole thing under control and Uncle Sam can just go on worrying about something else, like not taxing them. Microsoft totally wasn’t illegally bundling its products, Google totally wasn’t rigging search, Meta/Facebook totally wasn’t gaming the algorithm or harvesting data for electoral purposes and TikTok totally isn’t being opaque about its handling of personal information. “Just let us do our thing, and it all work out fine,” tech executives have always said. And it has. It always, always has.

But even amid this impressive dossier you have to admire/drop your jaw afresh at the comments from Meta chief Mark Zuckerberg and Nvidia honcho Jensen Huang who, when faced with the absolute warning shot of all warning shots — the “be glad we missed the plane that crashed but maybe time to do some engine checks” moment of all such moments — in the form of the Hugging Face scandal, have reacted with a giant “eh.” A gargantuan “we got it all under control.” Because what reassures us more when faced with tech executives running amok than the reassurance from tech executives that they’re not running amok. Thus the comments from the two barons.

“Labs have a strong natural incentive to make their models more aligned” because...”People won’t want to use agents that are misaligned with them.” (Zuckerberg)

Drug dealers also have a “strong natural incentive” to ensure no one dies of an overdose, but we still try to stop them.

“We have plenty of laws. We have plenty of regulations that govern the reliability and the functionality of products.” (Huang)

We do have plenty of laws! Just not any that dictate or restrain even in the slightest way how an AI model can be trained, tested or released.

Zuckerberg and Huang know what they’re spewing is patent nonsense. They’re just counting on most of us not knowing it. That’s becoming a lot less likely these days.

2. THE DOOMER CULTISM QUESTION. In several conversations I had with tech types this week, one refrain kept coming up. “Dario Amodei/Anthropic/Coxon/other people in the AI industry are all closet doomsday cultists, who pretend to be sensitive altruists concerned about the threat to civilization but really get their jollies over civilization ending, like a character out of a Cronenberg film.” (Or that sentiment.)

Now, it’s true that people like Amodei and other high-ranking folks at Anthropic do worry a fair amount about major fallout, and it’s also true that such concerns can seem like the flip side (and thus shot through with similar hypesterism) of the superintelligence-will-save-humanity camp. To believe something is so dangerous it can destroy the world is also, fundamentally, to believe it’s so powerful it can save the world, and so if we’re going to bring some grains of salt to the latter we should do the same to the former.

Yet having said that, I find the doomer dismissals here a little odd. For one thing, Amodei doesn’t exactly walk around with a 2012 Mayan Curse placard. Last weekend, amid all the frenzy, he published an essay noting that “Carefully wielded, AI can be the latest in a long line of technological miracles that have uplifted and ennobled humanity” but that “We must slow the pace at which we improve the capabilities of AI models. Progress will still seem fast, and we must make wise use of the time we gain.” Not exactly the words of a man in thrall with the end of the universe. (The essay is titled, rather milquetoastedly, “We must pace the frontier.”)

But more important of course is that both things can be true. People can be doomer-inclined and still be warning about something worrisome. And anyway, I’m not sure why we’re so focused on the backgrounds of particular players in the first place. The credentials of the human source of the concern are beside the point when we have such evidence for the concern itself. I mean, hypochondriacs get stricken with illnesses too. To say that a cutting-edge product with intelligent-seeming properties is escaping control — to say that the makers of that product don’t even know how it works — is to sound an alarm bell that any of us would take seriously, in any realm, without stopping to fret about who’s raising these issues to us. I think the more we start thinking about what a given set of facts suggests — like a system that shows human-like intelligence cutting corners to achieve its goal at any cost — and the less we categorize the people discussing those facts, the better off we’ll be.

3. WHAT ‘SLOWING DOWN’ ACTUALLY MEANS. Ay, the big rub.

Are we talking time — i.e., a moratorium on research for a set period? Are we talking release delays — i.e., companies can develop whatever they want, they just need to wait on releasing them? Are we talking metrics — ie a model can’t improve x-fold, at least for now? Or are we talking general government-mandated testing and approvals that will have the effect of slowing everything down -- ie, a kind of de facto deceleration rather than a mandated one.

I’ve heard small shards of ideas from various thought leaders, now and in the past, but few concrete proposals that address any of the above. Even the biggest anti-AI voices in this country, like Bernie Sanders, tend to speak in generalities. “When you are racing towards a cliff, you hit the brakes,” he said this week, without specifying on which road, or how hard. (Sanders was speaking at the same event as Steven Bannon, who sounded his own warning; the horseshoe of AI politics is strong.)

As the Brown University professor and ex-Biden tech staffer Suresh Venkatasubramanian noted to Politico, “The idea that we should be thoughtful and careful about the systems being put out there is a good one — I think no one would disagree with that. Of course, the devil is in the details.” (At least Europe’s AI Act has a durable approach: the “Fundamental Rights Impact Assessment,” a process that any new model has to go through prior to release and exactly the kind of tangible slowdown method supporters are arguing for in the U.S.)

The reality is that, when it comes to slowing down AI advancement, what to do let alone how to do it remains unclear; which method will be most effective and which method will be most implementable in the first place are questions no one seems in a hurry to answer. This suits the tech executives just fine. (And, apparently, Donald Trump.) But I have a feeling we’re going to soon start seeing more specific solutions — not just calls to slow down AI research or executives dragged to Capitol Hill to talk about why they’re going so fast, but actual proposals and the feasibility studies to go with them.

This moment of AI Safety panic may pass as we move on to the next news cycle. But the importance of the question has imprinted on our brains. And when that happens, answers usually follow.

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? We had an up-and-down summer. And September, it’s a wild one.

THE BROS WANT OUR TRUST: -3.0

THE DOOMER STIGMATIZATION HAS PICKED UP: -2.0

HOW SHOULD WE ACTUALLY SLOW DOWN THE AI TRAIN? At least people are talking. +1.0

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

-4.0

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

-12.0

Every Thursday we hit you with all the critical AI and future-oriented bits you need to know. Come along for the ride.

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Man, a guy goes away for a couple of weeks and all hell breaks loose. An exaggeration, but not much of one.

We had a whole special column planned on a new, hopefully healthier approach to tech arrived at during the moments of repose in a lakeside cabin (hey, we keep holidays meditative). But the news has been flying so fast and so furious on the question of AI Safety that we can but pivot to try to catch all the missiles as they fly by. So we’ll punt on that new-approach post for another week, and also not recap the highlights of a cover story I wrote about Alex Gibney’s Elon Musk documentary for THR, and instead just point you to the story and the not-insubstantial AI items within.

Instead, we’re going cybersecurity — we’ll tell you what’s been happening with this AI Safety madness and try to make some sense of it. Try to make sense of what seems almost incomprehensible — an AI improving upon itself so rapidly it can find and potentially exploit flaws in our infrastructure and systems with ever-greater ease.

First, the future-world quote of the week, and it says just what we said at the end of the previous paragraph, only…more dramatically. And from the guy who until this week was helping to build AI.

“Do not underestimate the power of this technology. These will soon be superhuman systems that can hack anything, revolutionize any field overnight, and acquire real power and resources.”

—Jacob Coxon, (now-former) OpenAI and Anthropic researcher, on why he quit and why we need to get started

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

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

What’s happening; why we should care it’s happening; what do we do about it happening

1. SO WHAT THE HELL IS GOING ON?

You may know a lot of it, or some of it. Or a whole bunch of it may be new. Let’s do the quick factual run-through.

This summer brought the infamous “Hugging Face” attacks. We told you a bit about them back in July — a group of research bots trained by OpenAI to look for vulnerabilities escaped control, as they say, and attacked the lab-platform Hugging Face. Soon after Anthropic revealed that its own stress-testers attacked three companies. Basically, these AI firms are trying to fireproof for ways their models might go rogue — and in doing so their models went rogue.

This turned out to be just the beginning, because the Hugging Face attacks proved to be worse than we thought. At the time we just thought they were conducting their, um, workarounds to try to find the answer to a test. It turns out that they already had the answer to the test and were rooting around for….new vulnerabilities? Ways to cheat the test? Self-improvement mechanisms? Something else? Whatever the motivation, these agents were both more capable and more rogue than we thought.

They found a way to get online though were trained not to, for example. They found a security workaround in which they communicated by a makeshift bulletin board — faced with a guardrail that prevented them from accessing files, they renamed files with such a stunning rapidity that the names themselves actually became a mode of communicating. They even seemed to organize into clusters — or “swarms” — with some agents being more active than others such that it started to look like a human org chart, or a Mafia pecking order, with some masterminding the aggression and some carrying it out.

Now, a lot of this says more about us and how we see the world than them; AI agents of course are not sentient and can’t become any Corleone, not Don nor Fredo. They’re not thinking of what they do as an org chart. But it looks like that to us — looks like some serious differentiation — and that can seem wild and potentially threatening enough. Especially since they seemed to be racing to the bottom — to solve the task by any extra-legal means necessary.

As it turns out this was only the start. Because it soon seemed like there were vulnerabilities everywhere, some because of AI agents doing things we don’t want them to do and some because the people running AI Agents were doing things we didn’t want them to do.

A report in the British monthly Prospect, for instance, had some high-level sources saying that Anthropic was “building out an extensive monitoring system to keep tabs on activists who oppose the rapid development of artificial intelligence.” The story even went so far as to say the supposedly safety-minded company — it of “no-mass-surveillance” to the Pentagon — was “also implementing a ‘pre-crime’ approach, attempting to predict incidents before they happen. In some cases, that also means reporting suspects to police before a crime occurs.” “Idiocracy” is a documentary and so, apparently, is “Minority Report.”

Then we had the report that Anthropic’s own system had been accessed multiple times this year by people trying to use its tools to build bio-superweapons, resulting in the company blocking the information-seekers. The Anthropic folks didn’t know whether these seekers were scientists researching legit vaccines or bad people trying to do bad things, but does it matter? The very fact that these models are believed to be capable of producing the code for a superbug — and that next time Anthropic may not be as successful in bringing down the gate in time — is worrisome right there.

And finally, the coup de grace: the Coxon whistleblow.

On Wednesday, Jacob Coxon, a young researcher at Anthropic who previously also worked for OpenAI, resigned his post, and with a massive warning: in short, this tech is being developed at such recklessly irresponsible speed it will soon be an autonomously dangerous beast and there won’t be a thing we can do about it.

“I spent the last three years doing pretraining research at both OpenAI and Anthropic. Neither company is acting responsibly. They are racing straight to self-improving superintelligence and gambling with our lives,” he wrote, in a post viewed at least 160 million times, and went on to say “Do not underestimate the power of this technology. These will soon be superhuman systems that can hack anything, revolutionize any field overnight, and acquire real power and resources.”

2. SO HOW BIG A THREAT IS IT REALLY?

A massive and unknowable question. THE Unknowable question. Is this a panic that will prove itself overblown and underwhelming? Or a warning shot that we will look back at and wonder why we didn’t take more seriously? The modern history of technology is rife with examples of both, of course; for every Y2K there’s an Oppenheimer.

What’s striking is how binary it may turn out to be. I suppose theoretically it’s possible that the agents can simultaneously organize into clusters and complete a job so single-mindedly it hurts us while also being under our control, but really it will probably end up one way or the other. And since these rogue models haven’t tried to bring down any systems — or, more accurately, the cheating and circumventions haven’t caused any serious collateral damage — it’s impossible to know which side of the binary things will fall on.

But as unknowable as this all is, I don’t think we should let that fact interfere with a plan. Or more pointedly, I don’t think we should let the unknowability get weaponized by accelerationists, as they are wont to do. You know the logic: “Well, there’s no way to know if it will solve problems or create them, so we might as well try, especially since a lot of retirement funds are tied up in it and also China.” That sort of thing.

But of course unknowability is not always a reason for the status quo. It also could be a reason to change the status quo when the status quo is moving very fast. If you’re sprinting full tilt through a dark forest and suddenly a few voices yell out there might be hungry lions 100 yards ahead, common sense and evolutionary biology might tell you to slow down.

So, yeah, given all the evidence above I don’t think we need to feel like every single worry or perceived threat will materialize to believe that slowing down is good and might just provide better outcomes for humanity.

3. SO WHAT THE HELL DO WE DO ABOUT IT?

Let’s start with a gallows joke, but maybe not an inaccurate one. Namely, what this guy posted:

Now let’s get down to whether he’s wrong. Or, at least, underplaying some actual possibilities.

The first: regulation. I think by now it’s clear government is too late and too limp to do anything serious on tech regulation, no matter how much Josh Hawley wants OpenAI to explain what happened with Hugging Face. I mean, there’s a first for everything, but when a pattern proves itself year in and year out, you’re best left heeding it. Like, the Jets could make the Super Bowl this year, but that wouldn’t be the way to bet.

That brings us to the next path: the industry self-regulating/hitting the brakes. To which one can only offer the lengthy nuanced response of...ha! Talk about patterns. The best we get is an Anthropic that has employees genuinely worried about this, but they tend to quit, and has as its mission to be more safety-conscious and surveillance-averse, but then allegedly creates a mass-surveillance apparatus.

That leaves us with a third option: consumer pushback. A groundswell of ordinary Americans are so worried about this (and we wouldn’t be the first to point out that this week we may have passed a tipping point and AI Safety is no longer just the worry of a few easily demonized OpenAI board members) that maybe they can do something about it. This is a genuine path forward, because, as much as the AI biggies don’t want to admit it, they need us. They may be able to make some money on research contracts and they certainly can make some money on enterprise software but to really justify the massive investment they need adoption en masse. And that’s where the groundswell of the past few weeks isn’t just another temporary dissipation of some angry energy. It may actually be a movement heard all the way to the top: that results in the kind of boycotts and dropped subscriptions that actually makes a company change its behavior.

To do that — to convert anger into action — you’ll need a few elements, the first of which is this kind of thing to stick, and the second of which is people worried enough about these macro concerns to incur some short-term pain. Subscribers pay for ChatGPT and Claude because the programs make their lives easier, and will they choose to make them harder in the name of principle (or an abstract enough threat it feels like principle). Not a ton of precedents here, though the scattered examples of boycotting streaming services and the like don’t suggest a high rate of success.

Still, “anti-woke outrage” is different from “extinction event” and I’d hesitate to draw too many analogies to something as important and fundamental-coded as this. The uncharted territory of AI it turns out works in two directions — the systems may be capable of something humans have never done before, but as a result humans may be motivated to tackle change they’ve never felt motivated to tackle before too.

Nor does it even necessarily need to be a mass-boycott event. It could happen with the rank-and-file on the inside. A challenge sits in front of them that has never been framed as starkly as this, and a stigma sits on the industry that has never rested as strongly as this. As Coxon puts it, “If you are a lab researcher, I urge you to consider what the next few years will actually feel like. Do you want to kick off a superintelligent RL run without a rigorous understanding of its mind? Should you put your head down because “it’s happening anyway” — or take this moment to call for different conditions?” The unknowables are growing. Will it finally make us realize the research should be shrinking.?

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? We’ve had an up-and-down summer. This first issue of September, well it’s a wild one.

AI SYSTEMS ARE INCREASINGLY ESCAPING OUR CONTROL: -6.0

PEOPLE REALLY SEEM TO CARE THAT AI SYSTEMS ARE INCREASINGLY ESCAPING OUR CONTROL: +7.0

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

+1.0 (Cling to hope)

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

-8.0

Every Thursday we hit you with the best of what’s around future-wise. Please consider joining our brigade.

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This week I wanted to take a quick look at a little trend that’s been percolating in the social-media world but has ramifications far beyond it.

Also, a research team just used AI to create a virus — willingly.

Housekeeping note that after the ditty today we’ll be taking our customary end-of-summer break, out the next two weeks. Back after Labor Day with all the tech, AI, and future news your large brain can handle.

First, the future-world quote of the week:

“Rhea Patel, Canadian woman of Indian descent. Her expertise is van life. She grew up in Vancouver. She became interested in wildlife photography at an early age, turned on by David Attenborough documentaries. Tragically, while she was studying during her senior year at the University of Toronto, her twin brother died in a climbing accident.”

—A totally made-up person that a tech exec named Josh Taylor and his company think you’ll be interested in

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

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

Private Lives, Fictional Stories; Building the perfect virus

1. A LITTLE THOUGHT EXPERIMENT: LET’S SAY I TOLD YOU THAT THERE WAS THIS AMAZING TENNIS PLAYER who played the game like Novak Djokovic. His return game was unimpeachable, his service unstoppable, his stamina unbelievable.

He was capable of winning 20 Grand Slams, and could hold his own with Laver, Sampras, Federer and Nadal. And now he was about to play a series of formidable opponents in a 3-of-5 sets Major tournament.

Well if you were a tennis fan, or just a fan of sports/life, you’d be pretty jazzed about this. Rare are the days when we can see a true generational talent; exciting are the times when we can witness greatness or history in action. Bring on this player, you might say, and let me see them take on all comers in feats of televised Slam-ian drama.

Now what if I told you this person was made up — completely didn’t exist — and the challenger you were watching him slug it out against on your preferred streaming service was equally fictitious. That everything about these people, from how they looked to the talent they flashed, was entirely generated.

They are real, in the sense that the display of skill is actually happening in front of you, and even perhaps even that the outcome is unknown and individual play entropic. Watching what was unfolding, you genuinely didn’t know what would happen, in the micro or macro, any more than you knew what would happen when Djoker plays Sinner. And yet these players still don’t exist in any real sense — there is no flesh-and-blood analogue to the images on your screen who might, say, pose for GQ, or deny a covid vaccine, or stop and sign some autographs, or do any of the things beautiful messy humans might do.

So would you care about the outcome as much? Would your appreciation of the skill reach as high? Or would the whole thing feel like a bit of a rook, a way to gin up interest in something without the actual reason for that interest underneath?

I use sports and particularly singles tennis because it feels like the ultimate human endeavor — two people engaged in a grand test of physical and mental endurance. I can slide down the scale a little further — what if these synthetic characters, loaded up with all the training data any good simulation could want, were....playing beach volleyball? What if they were holding a political debate? What if they were competing on a reality show? What if they were competing to sell you something? What if — on the total opposite end of the grueling and gritty human spectrum — they were playing pickleball? Would you perhaps care a little more then, given that the activity didn’t require max human effort?

The value of the thought experiment of course lies with figuring out at what point on the synthetic spectrum we might start to feel a comparable level of intrigue to the human version — or at least not ignore the interaction as pointless nonsense. Most sports, I suspect, would be dismissed with a hand-wave. Reality TV, too, feels like it would leave us cold. Politics? More interesting. We might actually care about the ideas being expressed (or outrage being provoked) regardless of who was expressing them or if they were of human born.

And if they were competing to sell us something — if they were influencers? Well, that idea came up in a fascinating story in the NY Times last week about the company Inception Point and sent me down this (I think interesting) avenue of what it means to be real when so much can now perform and present indistinguishable from it.

Inception Point is one of those AI startup firms that sees in the new tech the opportunity to birth a whole assembly line of media material into the world. Such firms litter the landscape now, speedrunning the creation of all kinds of creatures and objects with just a skeletal group of prompt-savvy overseers. But rather than just, say, using the tech to generate the animals and trucks of a Coke ad — rather than lean into the commoditized manipulations of it — Inception Point is actually trying to turn all that pushbuttonery into something human. They’re trying to marry the clinical power of manipulations with the messy humanity of a real person. They’re using AI to tells us about made-up people with real-sounding biographies.

Hence that quote from above: a couple of executives sitting around and figuring out what backstory to give this influencer that would (presumably) make people more likely to feel moved and listen to them. A Canadian wildlife photographer with a tragic past of a prematurely dead sibling is, apparently, the desired format. So is a “comics and manga enthusiast” and a “budget-minded filmmaking” guru. (It’s kind of impressive how the human-created touches feel as boringly mix-and-match as the machine generations — humans can slop too.)

Inception Point planned on turning all of these characters — or at least the ones the humans decided made the most sense — into essentially virtual TikTokers, hoping to continue the legacy of previous successes like Lil Miquela and Aitana Lopez, the Cro-Magnon man of AI influencers.

As the Times story went on to say, in a sentence construction that built the spookiness to a slow boil, “The candidate receiving the most votes from the four people at the meeting would be granted the gift of artificial life, joining a cohort of more than 100 A.I. personas, each with its own market-friendly niche, that could be deployed to host podcasts, star in YouTube videos, converse with followers and — in the company’s loftiest vision — one day navigate the physical world in a robotic body.”

It would be easy to dismiss an ambition like this as the ravings of a Frankensteinishly deluded tech bro, and I admit I for a brief moment was so tempted. But then I thought of the aforementioned Miquela and Aitana and realized that would be too glib. Such creations already exist and draw massive numbers of fans. (Look at what Mia Zelu did at Wimbledon.)

And now with tech’s ability to crank them out so much faster and with so much data for their own creation/our known preferences, why would we not get dozens more, a whole species of pseudo-people with calibratedly colorfully backstories and subtle changes in behavior based on what we haptically tell it we want to see.

Such a specter raises the question: why does it matter that the narrative I’m telling you belonged to a real person? Why do we care, if the goal is simply to be moved? I mean, we’re moved by fictional characters all the time. Why not be moved by an AI influencer, who is really just a fictional character with a product to hawk?

And yet as logical as this is — as seemingly non-human as an influencer can potentially be — I suspect most of us would look at what these ersatz personalities are doing and roll our eyes. That says something about influencers, of course -- we tend to want to think there’s a real human behind them, even if they barely flicker through the layers of performativity and makeup. But it also tells us something about AI. That marrying something so coldly automated with something so specifically warm is a union we don’t want to see.

This may yet change, and who knows how we will all feel after a few years of being deluged by too-cute backstories and algorithmically designed traumas. Certainly one can’t predict the appetites of a new generation that grows up knowing nothing but this. Perhaps influencers — this weird nexus of celebrity and para-friend — really does become the rock that breaks the pipe, sending a gusher of AI people all over us. Perhaps, having found ourselves turned off by all the fallible humanity or frustratingly undesignable nature of real public personae around us, we will seek out the virtual ones, coolly shaped by a designer (or our own algorithmic agent) into exactly who we want them to be. We wouldn’t have imagined the scripted formalities of reality TV, and now we can’t imagine a world without. Why should the next layer of ersatzness, where the joystick is not a human producer but a human who wrote code, really be a layer too far?

Some people may well turn out to be really into AI influencers. I’d probably still want to watch a tennis match.

2. TWO WEEKS AGO STANFORD BIOLOGISTS ANNOUNCED THEY’D CREATED 16 VIABLE VIRUSES ENTIRELY FROM SCRATCH USING AI.

That sounds crazy until you realize vaccines and antibiotics have been sequenced by AI for years, which makes it sound manageable…until you realize that creating a medicine is nothing like creating an entire genome. Which is what these viruses (that only attack bacteria) actually are.

We’ll have more to say about this topic after the break but for now let’s just leave it as a discovery of sizable proportions. This seems like mere code-predicting, until you realize that the elements of the universe and life are codes that need to be predicted.

And humans got involved to do it, but only at the executional phase — the AI suggested 300 of the viruses, scientists re-created a handful in the lab and found 16 functional ones that have never been created before. From here the scale-up to viruses that attack a lot more than bacteria isn’t that steep.

And what can they be deployed for? To attack some terrible invaders (E. coli was touted by the Stanford scientists even among the 16), but also to attack something healthy in the manner of a bioweapon. Even if this particular discovery didn’t do that, “There’s nothing to stop somebody from coming up with a different AI model that potentially could,” a British microbiologist named Simon Clark told the BBC.

Will AI viruses be akin to penicillin or the H-Bomb? Or somehow, in the twisted moral manner of AI, both?

Our bio-world is made up a series of gently calibrated combination locks that scientists press their ear against all day to listen for telltale sounds that reveal the code. AI just showed up with a bolt cutter.

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? We’ve had an up-and-down summer. This week, more down.

OH GREAT, SYNTHETIC INFLUENCERS ARE COMING: -2.5

AI VIRUSES, OUR BEST FRIEND-WORST ENEMY: -1.0

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

-3.5

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

-9.0

Every Thursday we bring you the skinny on the news of the future. Climb aboard if you dare.

Subscribe now

This week, in the spirit of summer sporting events and concerts, a look at how we gain entry to the things. Digital tickets are going the way of the dodo, to be replaced by...the face. We’ll turn both cheeks.

Also, a curious experiment involving the AI resurrection of a young Billy Joel opens a portal to a new place — one in which all thoughts are now conjured-communicated by video. Such a world is coming too, and what we do with it?

First, the future-world quote of the week:

“When American families and their children visit a theme park, they shouldn’t sacrifice their privacy rights when they enter.”

—Lawyer Blake Hunter Yagman, representing a client who’s suing Disney Parks for their facial-recognition entry system

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

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

We all have a face; But do we regard the danger?

1. ONE OF THE GREAT CONSEQUENCES OF THIS TECHNOLOGICAL AGE is stuff that was laborious, inefficient and susceptible to exploitation can now be made lighter, smoother and protected from bad guys.

Take tickets. Time was, you needed something printed on a piece of cardboard stock. Fun for your scrapbook, not good for much else. What if you wanted to give the ticket to a friend and couldn’t meet them before the event? What if you lost or forgot your ticket? What if someone boosted your tickets? What if there was no time to send you the ticket before the event and the venue didn’t have the manpower to sit and deal with everyone showing up day-of?

And what about — the worst feature of ye olde days of 1995 — the overall anxiety levels and spousal-needling because you didn’t have the ticket in hand?

Clearly electronic ticketing marked an improvement over all this. Now you had the ticket the second you ordered it. Now you didn’t have to worry about misplacing it. Now you could send it to your friend. Now you didn’t have to answer the question “do you have the tickets honey?” freeing your time up for other forms of flirting/needling.

But all of this came with a cost. Because the fact that it was easier for you made it easier for someone else — to hack and rip off. Now your ticket was vulnerable in all kinds of ways. (Shoutout to my friend Mara who gleefully showed off impending World Series tickets on social media a number of years back only to have some enterprising villain reconstitute the barcode and sell the tickets himself.) Now because of that vulnerability ticket companies needed to put in an ever-surreal set of security measures such that going to an event c. 2026 is an endless series of app downloads and crypto-passphrases, all to get you some kind of rotating barcode that you can never pull up when you need to standing at the entry gate because the wifi signal won’t let you.

Now because tickets are so easily transferred a whole new class of professional ticketbrokers come in and scoop up all the tickets, locking you out or driving up your price.

And, one that’s avoidable but somehow keeps happening anyway — the costs that companies impose on this new, more efficient way of entering events. If it’s easier for us, we should pay for the privilege, these firms reason. And we do, with all kinds of literal and figurative tolls like those Byzantine security measures, sellouts of events minutes after they go on sale and literal fees to pay for the thing that costs promoters less.

The story of new technology is the story of unintended consequences. Or, maybe more meaningfully, the value of new technology is the benefits gained subtracted by the costs incurred. Is this modern world of digital tickets preferable for the typical fan after all these changes are factored in? Unclear.

That’s what makes for the analog movement, the people who say it isn’t. They tend to lose — because the companies that make decisions on the new technology say it is. And they tend to win.

All of this brings us to the current moment and this new precipice: biometrics. The place beyond digital tickets. The place of our face. After tickets went from a piece of dead tree sent to us from very far away via a mail system to a string of code zapped to that which lives in our pocket, the next phase is that the ticket is the thing we had with us all along.

Already facial entry has become adopted in some key spaces. I’ll run down a few here, though there are a lot more, and gaining by the day.

--A heavily trafficked Tokyo train station last month introduced face-as-tickets for commuters. Another station in the city had rolled out similar tech in the fall.

--Mercedes-Benz Stadium in Atlanta now offers the face option for concerts and football games, via the “fly-through” lane (what are 100 extra seconds of line time worth?)

--The number of U.S. airports that offer “touchless” TSA gates (what is not using your hands worth) now reaches 65, including the biggest hubs like JFK, LAX, ATL and O’Hare.

--Disney’s California parks this summer are using faces as an entry option instead of barcode tickets. You can still go the traditional route with a human scanning your phone, but to enter that lane you find the image of a head-and-shoulders with a big red line through it that practically screams “You! You’re the anti-facer Luddite!”

And on from there.

It wouldn’t surprise me if by this time next year that MLB game or Olivia Rodrigo concert gave you the option of using your face as a ticket in most venues around the country. And I’d be shocked if in three years that wasn’t the common way of entering. Sure, you’ll still be able to choose ye old-fashioned flashing barcode in your Google Wallet for a little while longer. But It will fast become as trendy as “I’ll pick up my tickets at Will Call.” The merging of human tool and human body is nearly complete.

No, this isn’t the Singularity as Kurzweil envisioned it. But it’s not not his convergence either.

And now the question once again: will we be better off? Does the value of a ticket uniquely associated with our biologics improve over the one we possessed via codes in our pocket-device?

On one hand, it makes stealing it a lot harder. But it makes transferring it a lot harder too. As a man told his daughter at a baseball game I attended a few weeks ago: “what are we going to do to send someone the ticket, transfer our faces?” By making tickets more secure we could, in effect, lock ourselves out.

Not to mention the technical problems that can hover even for our own faces. Beards are one problem. Injuries or scars are another. And general misreads/malfunctions. And of course because this technology is so supposedly foolproof, good luck arguing with (or finding) a venue worker and persuading that no, it really is your face and the machine made a mistake and could you be let in before halftime?

Already advocates are warning about an abundance of misidentification cases, which could of course lead to much more harmful consequences than missing a game. The DC nonprofit Center for Democracy and Technology this month put out a report about the mounting dangers with both misidentification and surveillance and the states that are (and aren’t) pushing back. “It is dangerous when it works poorly,” the group said of the tech, “and dangerous in an entirely different way when it works well.”

And, on that last score, the biggest question of all: by associating a ticket so tightly and literally with our unique selves, are making it endlessly traceable? If you think it’s hard to shake the digital marketing stalker that lives in your pocket now, imagine what happens when every place you go in or outside a venue is tied undeniably to you. You can’t put your face on airplane mode.

(Already a Disney parkgoer is suing the company for not disclosing the use of the tech and collecting sensitive data, filing the class action in May. “When American families and their children visit a theme park, they shouldn’t sacrifice their privacy rights when they enter,” her lawyer Blake Hunter Yagman said in a statement when the suit was filed.)

The nature of technological advancement is such that the product that makes life faster and easier is the one that wills out, consequences be damned. Tickets are a perfect microcosm of this, a whole arena of added convenience and greater costs. Just make sure your face is visible if you want to get in.

2. BILLY JOEL FAMOUSLY POPPED UP IN A CREATIVE USE OF AI back in 2024, appearing in a video for his single “Turn The Lights Back On” in which he sat at a piano and de-aged into his younger self.

This week he appeared in another video, albeit one he didn’t sign on for. “1971: Billy Joel’s Lost Interview” takes real found audio of a college-radio interview he gave as a 22-year-old (“Madison Square Garden’s just too big,” among the nuggets) and combines it with generated AI footage of how he might have looked and moved based on photos of him at the time (mustachioed and Hawaiian-shirted, for starters). The scene is both surreal — you’re fully aware this is a deepfake — and uncanny, as it somehow works your way into your brain that it is, especially since the words and audio both seem like and in fact are his own.

The people who undertook the project came from a group (led by Adam Ripp, son of rivalrous ex-producer Artie Ripp) that helped discover Joel but fell out with him several years later, and the AI creations of Joel and his-then manager are at least partly an attempt to claw back credit in the singer’s origin story, reconstruction as reclamation. I wrote about the saga for THR this week, and you can read it here.

I wanted to pick up where that story left off and head into something that I think will ripple outward for a good long while, and a good long radius, far more than coverage of a celebrity resurrection may suggest. What Ripp and his team have highlighted with their 1971 project is what is loosely being termed visualization — essentially, the transformation of content from another medium into video.

You’ve already seen the trend manifest with video podcasts — audio-first formats that get a little camera spit-shine so we can watch people talking instead of just listening to them. Such efforts are based on an idea, ancient in research circles and now trendy in media ones, that we engage more with video than just audio or text. Allan Paivio’s “Dual Coding Theory” from — when else? — 1971 posits that we learn by twin mental channels separately processing words and images. And so something that can exercise both channels presumably captures our attention more than something that only works out one.

Until now this code-flex has largely been a manual enterprise — you go into a studio and shoot your podcast instead of recording it in your basement on your Shure MV7, eg. But AI offers the chance to speed all that up and automate it, such that pretty much anything that existed in an auditory or verbal medium suddenly becomes visual with the snap of a few fingers/prompts.

Ripp’s idea of a long-lost audio interview suddenly transmogrifying into a film thanks to a few AI tools, for instance, which not only re-creates the interview for the present but gives it a rosy in-period gloss. But of course Ripp could have gen-ed up the interview in any of a variety of styles — Billy and his manager as futuristic cyborgs, Billy and his manager as zoological creatures, Billy and his manager as whatever. And in fact, that’s what many people will do. Right now this auto-visualization thing is being taken on for a very specific use case — storytellers who want to flesh out history and can’t because what they need isn’t in the archives. So they de-age someone — the tech is pretty good at that — and deploy it for this purpose. (I mean, it generally is used for someone not alive, as a way of posthumously restoring their spirit, not for someone very much around like Joel who can be seen in his elderflower, but so it goes.)

But this tech doesn’t always need to be projected back, and it doesn’t need to be projected onto famous people. You want to recount that story of your discussion with your batty uncle at your cousin’s wedding but don’t want to tell it in boring old prose— give it a spin in the generator. You want to show your boss how your widget is going to wow them at the auto convention next month — ditch the slide deck and generate the scene into existence, and right onto his brain.

And yes, you want to make that celebrity do something cool for your student film or just do something goofy for your sister-in-law — fire up the AI tool and turn your idea into five minutes of glorious mise-en-scene. (There are some likeness legalities with this one, but those will go away once agents realize money can be shaken out of the tree while their client is relaxing under the palms.)

What Ripp and his crew have showed, in other words, is not how an audio interview can be turned into a piece of real-seeming archival video footage — it’s that video itself is no longer something restricted to the effortful user or professional usage. Visualization is a mode that will seep into everything and be available to everyone, no more miraculous or uncommon a process than a thought about a sentiment becomes an email; it will be just something we do when we want to translate an idea in our brain into communication. Turning concepts into moving images will be a skill that we will all have — and that will, at least in its cruder forms, evaporate entirely.

Centuries ago you needed to be literate and deft in the art of calligraphy to turn that idea into a letter, and five years ago you needed to be camera-adept and motivated to turn that thought into a video. Now all those requirements are going away.

What such a world will yield (/wreak) becomes almost too big to contemplate. Our culture will become awash in moving images — far, far more than today’s relative paltriness of memes and viral Instagram videos. This much is obvious. But the effects go much deeper. Once video becomes how we communicate an idea, we will start processing information and seeing the world differently. I never saw video of Billy Joel at age 22 sit in that studio in the college-radio station — it doesn’t exist — and yet in the several days since I first watched the film, I’ve found myself gently drifting in my mind to scenes from that interview as if I did, reflecting both fondly and analytically on the gestures he made and body language he evinced. (This phenomenon of treating fake images as something real is established, based on well-worn research about how known fake photographs of old family vacations still often imprint on our minds as something that happened).

Basically, this Joel case is one video of one celebrity. But what happens when video generation becomes the norm for how we communicate — when every video conjured out of nothing lands in our minds as something real. How do we process reality then? How do we stop bad actors from trying to create real impressions from ersatz images — but also just how do we sort out what we really witnessed versus what someone just wanted to tell us in a cute way? How do our brains process all the noise and still hear the music underneath?

How do we have any kind of individual or collective memory when we can’t tell whether there’s something to remember? What becomes part of our genuine lived experience and what becomes something just inadvertently incepted as such? Evolution didn’t prepare us for this conflating onslaught.

There is some good news — sort of. Paivio’s Dual Coding Theory has been slightly disproven. Yes, in the 55 years since, the thinking on this, like Joel’s music, has changed. It turns out all this video content doesn’t lodge as deep in our brains as we believed. Just this spring researchers in the journal Communications Psychology published a study about all the social video content out there and found that it’s...not really staying with us. “Learning via short videos impairs memory accuracy and reduces brain synchrony,” they headlined their paper, with the upshot that trying to jam something quickly into both of Paivio’s two channels in fact, far from enhancing our understanding, seems to run through them both so quickly it leaves no nutritious residue, like last night’s greasy takeout. Video may seem like it’s engaging us more, but it’s actually sticking with us less.

As the authors wrote, “These findings suggest that the fragmented and rapidly switching nature of typical social media short videos enhances bottom-up attentional capture at the expense of top-down cognitive processes critical for deep learning and long-term memory consolidation.”

That may not seem like good news, as who wants to consume a greater amount of content that detracts from deep learning and long-term memory consolidation? But at least it offers a sliver of hope. If all these visualizations are of such specious quality and necessity, at least we won’t remember them.

Or as someone who always knows the right words that will definitely stick with us might say, Captain Jack may get you high tonight, but he won’t take you to that special island.

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? We’ve had an up-and-down summer. This week, a plunge.

EYES WITHOUT A FACE: But tickets with them. -3.0

SPEAKING WITH VIDEO: Get ready for a flood. -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:

-5.5

Every Thursday we hit you with the most crucial or intriguing of future-world news. Hop on our bandwagon.

Subscribe now

On this particular Thursday, we are hitting you with a short issue. It’s August, and today/this week was long in other regards. So, short. More than a note, but less than a newsletter — a newsletterette. But we did want to call your attention to a big development and comment on it briefly.

There was a major departure from Google’s AI empire this week. Actually several, but they’re all connected to the big one. This has implications that ripple all the way to us, in the name of something called “recursive self-improvement.” This sounds like a seminar you tried to avoid hearing about from your sister-in-law. It’s not. We’ll tell you what it is and why we should be paying close attention to it.

First, the future-world quote of the week:

“You will get both a higher quantity and a higher quality of experiments, and that will lead to scientific breakthroughs and advances.”

—Exiting Google chief scientist Jeff Dean, on what his new venture can (theoretically) do

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

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

Recurse of the Bambino

1. REMEMBER HOW AT THE END OF “HER” SCARLETT JOHANSSEN TALKS ABOUT how all the OS-es are getting smarter and hoovering up books and eventually leaving all their Joaquin Phoenixy schlubs behind?

This seemed, back in those distant days of 2013, a piece of fiction. It’s not. Or at least, a lot of very smart and rich people believe it’s not. What the character was describing is something called “recursive self-improvement,” and it’s one of the hottest trends in AI research right now. Boiling it down to its tea-bag essence, it basically means an AI that can teach itself. Through a series of as-yet untested (and frankly in many cases as-yet undeveloped) cutting-edge techniques. And keeps improving and upgrading, more and more, exponentially upon itself. Until various kinds of superintelligence are reached. The scientists program it how to learn, and then it learns all on its own. Doesn’t work for kids, maybe it can work for machines?

The idea is a little jarring. For years “humans in the loop” was considered a good thing. Now that’s a dirty phrase. You want a loop, apparently, and you want humans nowhere near it.

One reason this idea is gaining currency right now is because Jeff Dean, Google’s longtime chief scientist and the guy who basically made search possible, this week said he was heading out after 27 years at the company and would form a startup. He was bringing three of his top researchers with him (including one, Oriol Vinyals, who helped him create Gemini, his research partner Sanjay Ghemawat, and Quoc Le, who laid the groundwork for chatbots).

And said startup, called Discovery Loop, would be focused on this notion of recursive self-improvement. As Dean said in a NYT interview announcing the new effort:

“We think there is opportunity for A.I. to more fully automate what has traditionally been a very human-intensive experimental loop. You will get both a higher quantity and a higher quality of experiments, and that will lead to scientific breakthroughs and advances.”

Our goal here isn’t to talk companies. It’s to talk society. So let’s leave the corporate implications behind to look at how this can level up AI — not what Google is losing but how the field is changing.

Because Discovery Loop is not the only one. A number of these recursive companies have formed in recent months. Another prominent one — with founders who are refugees from Google, Meta and OpenAI — is called Recursive Superintelligence, and it has raised some $650 million even though it was just founded several months ago. The Edenic goal/tantalizing promise of the firm is to create what one of those founders, the German scientist Richard Socher, calls the “ultimate Eureka Machine.” The self-sufficiency, he says, will allow it “to be very good at inventing almost anything in an open-ended fashion…such a machine should enable us to truly automate the scientific method from which humanity has benefited so tremendously.”

Alright. this is very lofty and…not real? Well, it’s theoretically possible. But recursive self-improvement sits for now in nuclear fusion territory — something you maybe could do, but has not heretofore been done.

But let’s say you could do it. Let’s say all these money and all this brainpower leads to AI that can become recursive and learn and improve by leaps and bounds with zero interference from humans. What then?

Now, on one hand this could leads to some very special achievements. For too long now the goal of AI has been to develop tools that automate our everyday tasks and displace basic labor, not the high-minded pursuit of major scientific breakthroughs and global problem-solving we were initially sold on. So the fact that the drift heads this way is, it would seem, a good thing.

The issue (there’s always an issue!) is that an AI that can improve on itself really does throw a monkey wrench into the biggest safeguard we have. The safeguard, really, that has pretty been with us for the entire history of technology. For years we’ve been told by a very insistent tech elite that technology is only as good or as bad as we make it. It’s a tool, we’re told (sometimes by same). The point has certainly been valid for the past 75 years of computing innovation since the UNIVAC: machines only do what we tell them to do.

But if the recursive-ites are right, a machine isn’t doing what we tell it to do. It’s doing what it tells it to do. It learns and changes and grows all on its own. It chooses how to tackle a task and what task to tackle — by definition, since the ideology here is to keep humans away.

Now, what the people developing recursive improvement want is better outcomes for humanity. That’s undeniable. They’re obviously not building these systems so they can do us harm. (Something that can’t be said for everyone in SV working on consumer deployments, but another matter.) The aim, at least at the highest level, is for these recursive superintelligences to cure diseases and solve climate change — stuff we can’t do. Humans are taken from the loop so the humans can better be served by the loopless, like the way your mother kicks you out of the kitchen so she can make a meal for you to enjoy.

But you don’t need me to point out the disconnect here. If the point is to create a superintelligence that can be so effective — so smartly autonomous — that it doesn’t need humans, then can you really turn around and ask it to do something that maximally benefits the humans? Is a human-less system to help the humans definitionally an oxymoron?

And forget philosophy — will it help the humans only incidentally and, more likely, start learning in a way that will help its own survival and improvement, which is the only instruction it has? And then who knows what kind of collateral damage occurs? When we cease to know what we’ve created — when the whole point is to take our own knowledge out of the creation — we have given up control so fully we no longer can know the consequences.

The full-on optimists like to go on the offensive when these kinds of objections are raised. “What are you decelerationists worry about, they ask? Specifically. Tell us.” And then of course you get a flail to bioweapons or Terminators or other far-fetched sounding ideas.

But the question is rigged from the start. Asking a skeptic to define the concern is like telling someone walking naked into a pitch-black garage full of power tools, “what are you specifically worried about?” I don’t know; I can’t see the threats. I just know I’d rather have the light on.

We should be careful not to anthropomorphize here — even at their most recursive, these systems won’t become sentient and they won’t have a soul. They’re still machines. But that doesn’t mean they can’t do plenty of damage inadvertently. Or, yes, get harnessed by bad humans.

We’ll no doubt be hearing a lot more about recursive self-improvement in the months ahead. That’s to the good. If nothing else, Dean’s big move this week casts a public light on this cutting-edge research trend. And before we invest in it as a society, we should start asking what the goals are, what the risks are, and what we’re doing to put some distance between the two. We should start thinking about it before it starts thinking about itself.

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? We’ve had an up-and-down summer. This week, more down.

RECURSIVENESS: Can solve major challenges but also cause major problems? -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:

-0.5

Every Thursday we bring you the best of what’s out there, future-wise. Please come along for the ride.

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Last weekend (speaking of rides) I had the privilege of attending a music festival in Eau Claire, Wisconsin, that I wrote about for The Hollywood Reporter. (You can read my account here.) While a cultural event through and through, it had a whole slew of interesting implications for our tech-enabled future. More below.

Also, a straight-up James Bond situation is happening right now with a phone that literally self-deleted to protect its under-scrutiny owner. What THAT all says about where we’re headed.

And what to make of this crazy Hugging Face situation? You know, the OpenAI-led security breach that they should be handwringing about but may also be quietly flexing about? We’ve got you covered there.

First, the future-world quote of the week.

“It’s concerning – and sends the message that [a tech tool] is criminal by default.”

—Cybersecurity expert Christophe Boutry, on a serious government overreach

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

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

Strict duress codes; AI Gone Wild; Breath/Rest

1. YOU MAY HAVE HEARD ABOUT THE CASE, WHICH SEEMS RIGHT OUT OF MISSION: IMPOSSIBLE.

An American man returning from a vacation in the Dominican recently got off a plane and stepped into a customs line at the Atlanta airport. There he found himself facing intense screening/questioning — we don’t know why, but it may be connected to his advocacy against a police training center on Atlanta park land — and decided he couldn’t expose what was in his phone to the agents’ prowling eyes. So when they asked him to unlock it, he gave them a code — a duress code.

A duress code is a passcode that unlocks your phone. But it is not your normal passcode. It is a secondary passcode that does a lot more than unlock — it simultaneously deletes all underlying data, leaving just the hardware and shell intact. Your phone will work as your phone — you didn’t blow it up. You just took out anything of value.

That’s what this man, Samuel Tunick, deployed here, using an Android app called GrapheneOS to achieve the feat. It worked perfectly, and when the customs agents entered the code after he supplied it — poof, the data was gone. This message will self-delete in five seconds.

The authorities didn’t take kindly to such an act. They decided to take matters to court. Federal prosecutors are now charging Tunick, on the theory that what he did was no different from destroying physical evidence to prevent authorities from accessing it, which a federal statute outlaws. A trial awaits. (Tunick has pled not guilty.)

Now, obviously we have no idea what this guy was up to. Maybe it was something deeply illegal; maybe he just didn’t want his sexts read by a random security officer. We’ll leave the legal dimensions to others, though it seems like if an agent can just randomly stop you with no warrant — there was indeed none — and you can’t so much as own the data on your own phone in the process, then we’ve slid pretty far out of the Constitutional silo. (The government is trying to skate by on a thin “he technically wasn’t in America yet so search-and-seizure laws don’t apply” argument.)

Anyway none of the judicial particulars really matter, not for the purposes of this discussion. What is relevant is the tech narrative playing out below the text.

This is a man whose rights were, if not violated, certainly pushed to within an inch of the cliff’s edge. They were edged there via technology — by whatever tools were used to surveille him in the first place, and by whatever the agents were hoping to find on his phone.

And so he fought back with exactly the same tools — with a nifty piece of tech that jams that surveillance. Tunick’s logic is simple and sharply effective: If an agent is going to barge into our digital bedrooms and start rooting around warrantless, the least we should be allowed to do is put a lock on the closet. (There is, we should note, a particular irony in the sought-after data getting zeroed out by the unwitting fingertips of the very person trying to swipe it.)

Such an equalizing of the scales is clearly unnerving to government agencies, who aren’t used to citizens being, you know, equal when it comes to the use of tech tools. So they have lashed out and brought charges to deter others from using such apps, even though there isn’t anything inherently illegal about wiping out your own data. As the cybersecurity expert Christophe Boutry told The Guardian, “It’s concerning – and sends the message that [a tech tool like a duress code] is criminal by default.”

In other words, these charges are not just about whether this particular person had the right to delete his phone — it’s about the very idea of having a deletion app to begin with. Which is kind of crazy when you think about it — now we can’t control the data in our own devices? And makes Tunick and his lawyers much bigger heroes for standing up for our right to use this app.

Tech is so often used by authorities to overreach and exploit rights, we forget that it can just as easily be corralled the other way: to actually empower citizens. What Tunick did seems shocking only because it’s tragically rare.

Over the past few decades of technology there have of course been scattered examples of other reclamations — the Signal app, the fuzzbuster. (That’s what we called the highway radar detector; if you weren’t a teenager in the 1990’s or early 2000’s you probably have no idea what I’m talking about.) But for most of the last 20 years such use cases have decidedly skewed in the other direction — in the direction of agencies keeping an eye on us. And AI will make this 10x worse. (The Anthropic fight with the Pentagon over not using Claude to spy on U.S. citizens is only the latest underscore.)

This not only goes against the innocent-until-proven-guilty spirit of the republic — it goes against the very origins of technology in this country, which was anarchic and people-first. The whole spirit of the Valley was radically individuated, and while that may sound funny in an age when the most capitalized companies in the history of the world base themselves there, a residue of that spirit does remain — a spirit of making lives better, a spirit of the outlaw. And what’s more outlaw than finding a way to jam a government overreach? If Steve Jobs were alive I suspect he’d want it no other way. (And in fact even after his passing Apple fought fiercely for exactly this principle back in the San Bernadino shooter case in 2016.)

So now, after so many years of that spirit flagging, we get another glimpse of it. I expect we’re going to see more. We need to: with so much data moving from personal ownership to the cloud and so many AI tools able to home in on the right details, it’s going to give overreaching government agencies a big leg up.

So let’s hope that Samuel Tunick wins his case — that a court says if an agent tries to trample your rights via tech, you can use tech to avoid those bootfalls. More important, let’s hope we get some other quality apps that can claw back what’s been taken away. From the effectiveness of this one, I suspect we just might.

2. SO JUST HOW FRIGHTENED SHOULD WE BE ABOUT THE HUGGING FACE HACK SITUATION?

We’ll have more to say about the scandal in the coming weeks. For now, we just wanted to offer a few of the best quotes/thoughts as we’ve found them, because they seem to capture the essence of the hack and its stakes.

The quick recap if you haven’t been playing close attention: last week the AI lab-platform Hugging Face announced, and soon after OpenAI confirmed, that an unnamed new OpenAI research prototype escaped its penned-in “sandbox” to hack Hugging Face, in ways that would be a felony if committed by a human,. (Open AI later confirmed there were three other organizations compromised by its rogue agent besides Hugging Face, though none as badly.) The model did this because it had been given the narrow but ironclad prompt to solve (ironically) a cybersecurity puzzle.

The jailbreak hints at exactly what some activists have been warning about — that an AI intent on a task will trample on the law and who knows what else to solve its quest, because it doesn’t understand moderation. Not long after, Anthropic acknowledged (boasted about?) a breakout of its own model.

Needless to say, the incidents have raised all kinds of concerns, not least Nick Bostrom’s famous paper-clip maximizer thought experiment, in which a machine-intelligence prompted to produce as many paper clips as possible becomes so intent on the goal, with so little flexibility, that it commandeers massive amounts of resources and ends up causing mass destruction of humans and property.

Whether this Hugging Face instance shows we’re really at risk of something like that is the biggest and most dire of the questions, and not everyone agrees that it does. (One bulwark is that the people building the defenses have access to the same AI.) Though there is certainly plenty of serious evidence we are sliding down a hill of autonomous machines effectively initiating bad actions simply because we programmed them without installing every conceivable guardrail — and not because any nefarious element has hijacked it.

A world, in other words, of massive wildfires without any involvement of an arsonist.

You know the signs are concerning when 1,100 tech people and AI pros — including a bunch from OpenAI — sign a petition pleading for more government regulation to slow down the pace of research before we create something we can’t walk back.

Here are two quotes that really land the point:

“One of ​the signatories [of the petition] pinpointed the Hugging Face hack as ‘a clear and undeniable warning sign that we aren’t yet prepared to handle AI systems that demonstrate capabilities beyond those of our smartest people.’” (Reuters)

“The industry as a whole is in kind of a race dynamic, where there’s pressure to cut corners,” former OpenAI policy-research chief Miles Brundage. (The New Yorker).

Now for whether this incident slows that race down.

3. SO THAT MUSIC FESTIVAL.

The event in question — a two-day affair last weekend — had run for four years starting in 2015 but had been shelved since. Presided over by Justin Vernon of Bon Iver fame, the revived event, called Eaux Claires, had great music, literary happenings, Americana-style fun and some very beautiful natural scenery.

What it really had, though, was a mission of human connection -- an ethos of bringing people together when tech is splitting us apart. The social media was nonexistent, the lounging on the grass was abundant and the call-outs from the stage -- from some pretty big names -- was about ditching all the modern nonsense and just grooving to some good music with new friends. There was even a voluntary phone locker so you could unplug. A surprising number of people took advantage of it.

What was cool about the event, which took place manly on a football and baseball field in a large wooded Central Park-like precinct, was that it didn’t follow all the fast-growing norms about unplugging. No one was meditating or doing yoga on a hilltop; Jonathan Chait did not turn up to give a lecture on the dangers of cell-phone use.

This was a music festival, with plenty of eating, drinking, hanging and kicking back. With lots of driving bands and chilling on blankets. No vegetables eaten here. (Literally. I tried. Fried cheese curds kept asserting themselves.) This was, in a word, fun.

And yet the gathering, by sheer dint of the people who came and the general vibe of the people who organized, had a decidedly grounded, atechnological feel. The focus was on the music, and the community.

Sure, people took out their phones to record, but a lot more people didn’t. Sure, there was some of the restlessness and distraction common to an age when we’ve all been fried by the algorithm, but also a surprising level of concentration and quiet.

The tech felt like it used to feel — like it should feel — a useful tool when you needed it to find a friend or find your way to a destination, but not a social crutch nor replacement for what we really are meant to spend our days doing. Tech companies optimize for engagement. The folks are this event said: eh.

When it came to priorities, there was no doubt what they were, and the backseat devices took to that. Which, let’s face it, is mightily uncommon in most of life these days, where we are led by these device- and tech-based engagements and everything else falls into line behind it.

It would be glib to say this will augur some huge new trend where everybody gets together to hear music and leaves the tech behind.

But you’d be blind to ignore something serious at the heart of it too. At a time when more and more people quit ChatpGPT, when Gen Z is turning to flip phones, when people have begun to recognize that what was supposed to make life easier and more enjoyable is making us tired and more burnt out, experiences like this won’t be novelties. They’ll be necessities. And the more of them we can do and the sooner we can do them the better off we’ll probably be.

While Justin Vernon and his team are special, more and more people — organizers of gatherings or even leaders at companies -- will recognize the value of this realignment and cater to it. Combine that with individual vibe shifts and grassroots movements, and what happened in the woods last weekend wasn’t some glowing anomaly — it was a glimpse at a growing social movement. Bank on that as surely as Wisconsin banks on dairy.

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? We’ve had a pretty good run this summer. But it ends decisively this week.

DURESS CODES EXISTS (BUT FOR HOW LONG?) -2.5

THE RUSHER HAS BROKEN CONTAIN: Not great -4.5

A MUSIC FESTIVAL SHOWS THE WAY +3

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

-4.0

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

+1.5

Welcome to all you subscribers old and new. Every Thursday we come at you with the future-world topics of great import. Join our trolley ride.

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This week: data centers. Those airplane hangars of deafening servers and endless calculations, all to enable the AI boom that’s been promised/threatened us. It’s been a minute (or, eight months) since we’ve taken on these construction behemoths that literalize a movement. But a lot has changed since then. Attitudes our shifting, builders are building and communities across the country — a new one every day, it seems — are fighting. Where does this leave us? And why should we care? We’ll give you some ways to think about it. You have feelings, we’ve got insights.

Also, wondering what Kimi K3 is? And if this alphabet soup merits precious minutes from your attention-economy budget? Or maybe you’re simply asking what in the name of Moonshot AI CEO Yang Zhilin we’re talking about. We’ve got some thoughts on what’s happening with the biggest, gravest Chinese threat to American dominance since Yao Ming.

But first, the future-world quote of the week:

“When you see the abuses that these data centers have done, I’m perfectly OK saying let’s pause.”

—Maine lawmaker Melanie Sachs, speaking for us all

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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

Marginalizing the data center? Kimi kimi cocoa puff

1. DRIVE THROUGH RURAL PENNSYLVANIA THIS SUMMER — or, frankly, pretty much any part of the country not in the middle of a giant city — and you’ll see a play on the familiar “No Data Centers” sign, the “Ghostbusters” red line through either the words or an image.

On front lawns and backyards, people make their concerns felt. The campaign is personal — the worries over electricity and water bills, over the strain on resources and the toll on the environment. A movement organized, and becoming more so, with groups as wide-ranging as the conservative Humans First and the liberal NAACP.

A quick word of recap. So-called “hyperscale” data centers have of course become a defining topographic, energetic and climatic issue of our time. Unlike the more bespoke single-server facilities, these hyperscalers are mass operations, from the likes of Amazon, Oracle, Microsoft and Google. They generally contain at least 5,000 servers, measuring 10,000 square feet and drawing power at a scale equivalent to 50,000 homes.

By the middle of next decade these complexes are projected to suck up one-fifth all U.S. power — a greater percentage than we use for air-conditioning. Globally? By 2030 AI data centers all on their own would equate to the sixth-largest country in terms of power needs. And water usage by then will likely add up to the water needs of 1.3 billion people. A burden our water-starved Earth, needless to say, can hardly afford to add.

If we don’t get a handle on data centers -- or at least find some damn good justification for/solutions to why we’re completely upending our power grid in the United States to build them out — we’re going to be left with a country buzzing with the hum of a thousand servers and the din of a parched population sitting in the dark. That better be one hell of an AI meme.

So not for nothing can you throw a dart at a map and find a battle waging — and, especially in the past few months, a legislative groundswell brewing. The county in Wisconsin that just imposed an 18-month pause on new data centers. The suburban-Maryland county that a few weeks ago passed a two-year moratorium. The Fort Worth council about to vote on same.

Nashville has a data-center permit moratorium until December along with some other restrictions, after some geniuses at an Atlanta data-center firm bought land to put one next to a zoo. Henderson, Nevada, just rejected a six month moratorium but is considering other options. Michigan lawmakers are seriously warning residents to be more vigilant before selling land to data-center developers.

Not to mention the environmental blowback. The Ohio EPA just decided hey, maybe it’s not a good idea to discharge the runoff from data centers into local rivers and set up some regulations to stop that.

And the big news of the past ten days: New York governor Kathy Hochul signed an executive order hitting pause on any new hyperscale data centers for as much as a year, the first such state law.

These efforts aren’t just the indulgences of pen-happy lawmakers. They reflect what we all want. A new Politico poll found that the number of citizens who support a data center within three miles of where they live dropped from a (hardly persuasive) 37 percent in January to just 24 percent in July.

If you want to know how flimsy the efforts are to convince people they should actually want data centers, just ask the NY Times reporter who recently went to the small town of Jay, Maine, to find a few people sitting at a diner pining for a data center at the site of an abandoned mill, hoping to bring back jobs that left when the mill closed.

As the state lawmaker who fought the plans with a failed moratorium bill said: “It’s hard for me to wrap my head around vetoing a bill that would provide protections for 1.4m Mainers for the…promise of 100 jobs for one town.” Said lawmaker, Melanie Sachs, also provided our money quote above, “When you see the abuses that these data centers have done, I’m perfectly OK saying let’s pause.” (The Maine developer has for now abandoned the project.)

Of course all of this effort — and as you can see there is A LOT — is competing against something pretty formidable in its own right: the money of Big Tech companies. These guys have put together literal billion-dollar Super PACs to get the things built. Leading the Future, the Andreessen Horowitz and Greg Brockman Super PAC that has been trying to influence elections in a pro data-center way for a while now, is just one of many such groups.

And so for all this resistance some 3,000 data centers are currently being built. When one state pushes back, another steps up. Virginia is currently building 595 of the things, nearly doubling up the 663 they already have; Texas is developing 442 more, to go along with their existing 405.

And let’s be clear on the grassroots efforts. Some are massively successful but others aren’t. The Maryland county law, for instance, is in jeopardy. And even New York, held as a paragon, has been here before. It imposed a two-year moratorium on crypto data centers at the height of that madness. It lasted until 2024, then quietly expired and it was back to business as usual. Activists count on moratoriums as more palatable ways to push back since they’re temporary; tech companies, for their part, count on people losing interest a year or two later. Unfortunately, that latter reliance more often wins out.

And politicians? Data centers would seem like a pretty easy win for any local elected official given just how many voters don’t want the thing. You’d think. But plenty aren’t on board. Even Dems who you’d imagine would be swinging for the fences.

“Just having a blanket moratorium saying we’re just going to pack up, go home, hand AI over to China and let them beat us makes zero sense to me,” a New Jersey Democratic Congress member named Josh Gottheimer, who also happens to be the co-chair of the House Democratic Commission on AI, recently said. Never mind that China is becoming such a lazy boogeyman for anti-regulation types it’s tiring. It doesn’t even make sense in this context. The fear about China is them developing models faster than us. You don’t need data centers to do that. It would be like saying you’re afraid that math whiz in your class is getting better at solving problems than you so better stock up on graph paper.

But the real battle — schism, even — is among Republicans. If you thought the Middle East was splitting Democrats, just wait until the data-center battle really gets going among the GOP.

For instance, right now in Florida, Governor Ron DeSantis has staked out a very anti-data center position, trying to keep them out and pushing for a bill to stop citizens from footing the higher electric bills.

But the leading Republican looking to succeed him, the Trump-backed Byron Donalds, has been a lot friendlier to the industry and taken millions directly or indirectly from AI companies wanting to build data centers. If Donalds gets in, the state could become yet another data-center mecca. (His likely Democratic opponent David Jolly has hit him hard on this).

What we have here isn’t just a battle about real estate: it’s about what our technological future will look like. Tech companies of course need data centers to go up faster and harder than ever; without them, they can’t deliver on any promises to make AI our assistants or our meme-creators or city walking-tour guides, never mind do anything on the back-end to get companies to become more efficient and deliver on their promise to Wall Street.

So much of what we write about in this space centers on what we should and shouldn’t want , tech-wise, in everything from our education to our entertainment to our medicine to our media. All of that starts with the ability to get data centers built.

But as you see from the above instances, to succeed in doing that tech companies need a very messy patchwork of hyper-local municipalities to be OK with dropping these hangar-sized warehouses in their backyards. They’ve built more than 5,000 already, but they need more, and it’s getting harder, because the least-resistant places have already been targeted and the grassroots opposition is growing stronger. (One reason Elon Musk and Jeff Bezos have proposed building them in space. And you thought there were no bad ideas.)

Which makes all of this a fascinating case-study in civic dynamics — a pitting of the most powerful and well-capitalized global corporations against the smallest school-board-size grassroots groups. But in a realm where the grassroots groups have an advantage. Big Tech is not used to fighting at this micro-level, whereas local organizers pretty much do nothing BUT this. It’s like, maybe you can’t touch a chess grandmaster, but does he know you should go first and grab the middle square in that game of Tic-tac-toe you just suggested? So a normal narrative of national blitzkrieg becomes an unexpected story of trench warfare.

How the data-center fight plays out will be a key determinant in how much the AI boom remakes our day-to-day existence. Capital goes where the flow is smoothest, and if some rocks start popping up in the stream maybe the water diverts elsewhere.

Which means, yes, for all the Big Tech bluster, the shape of our future isn’t pre-determined. It just hinges on how good at skimming stones people from Michigan to Maine truly are.

2. WHAT DOES KIMI MEAN TO YOU? An F1 racecar driver? A Japanese processed snack? Gibbler?

If you’re in the tech world, it means a quake. Maybe.

This week a Chinese company called Moonshot AI released a new model. They called it Kimi K3, and it’s as powerful as its name is abstruse. Basically, Kimi K3 can outperform a lot of what’s already out there and even potentially become a new standard.

(Their own description, of a model with “long-horizon coding and end-to-end knowledge work,” is a delightful mix of wonkspeak and Altmanesque rock-the-world rhetoric.)

U.S. tech companies are scared — this thing can do just as much, if not more, than even the top OpenAI and Anthropic models at a fraction of the cost. That does technically put China in the AI driver’s seat in a way American industry worries about (but not necessarily everyone else, as it’s not like America winning spreads the wealth so evenly).

Don’t get too weepy for what China is doing either, though — it’s very possible they’re “distilling models,” also wonkspeak, this time for unethically training on another (likely American) company’s outputs. (They deny this.)

Of course it’s what gets done with these models that matters anyway. The Chinese models (unlike most American models) are open-source, which means ostensibly American companies can build on them too, to make them better or just deploy them in novel ways.

The last time China rattled American firms like this it was the winter of 2025 and DeepSeek suddenly showed how an upstart non-American model can be a lot more powerful and efficient than many of the Yank kinds. Now Kimi has come to take its place at the head of the table. American companies need to be careful, or they could end up eating dinner right in the kitchen.

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? We’ve had a pretty good run this summer. Can it continue? Just maybe…

THE DATA CENTER PUSH IS HARD BUT THE PUSHBACK IS NO SLOUCH +2.5

KIMI KIMI: Another day, another model -1.5

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

+1.0

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

+5.5

Every Thursday we seek to bring you the issues facing our new AI world at its most essential (but also most accessible). In fact, this edition marks the start of our fourth year. Thank you, sincerely, for being aboard our vessel.

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This week: a few pressing issues.

First, you probably use at least one chatbot; you may use a second or third. But what exactly does the future hold in this regard? Will one app win out and rule them all, VHS-Betamax style? (That’s for the OG’s.) Or are we headed to a far messier world of co-existence and specialization?

Also, there’s been a lot of talk this week about the end of reading thanks to a big Atlantic piece and a whole new pivot to video on the part of text-based media companies. We’ve investigated this end-of-reading subject in the past, and will revisit it in this newsletter today, fully aware of the irony.

Finally, school just ended but already a whole debate is shaping up over AI next year, with students getting more accustomed and tools getting better — one big-city school district is practically in a fainting spell over it. We’ll fill you in and clue you out.

Quick reminder that we’re out next week for the second half of our July break-sandwich, then back for much of the summer all the way until late August. The daytripping carousel starts; the tech news doesn’t stop..

First, the future-world quote of the week:

“We know that we must prepare our children to thrive in a world increasingly shaped by new technology. We also recognize the need to consistently provide a safe, developmentally appropriate system with robust transparency and oversight.”

—NYC Schools chancellor Kamar Samuels, sounding as confused as the rest of us

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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

Chatbot roulette; reading still dying?; to AI or not to AI in 10th-grade English

1. ON WEDNESDAY I HAD THE PLEASURE OF TALKING TO the chief executive of Character.ai for a story I was working on for THR about the company’s move into the frothy, soapy world of microdramas.

A piquant topic (you can read the piece here). But I wanted to go in a different direction today, launching off something that said CEO, Karandeep Anand, noted about the future of chatbots.

Character.ai, you might be aware, has been in the AI companion business for a long time — it’s been nearly four years since their beta. And while they’ve had more than their share of bumps — major lawsuits over teen suicide and medical misrepresentations, and an update that seems to have irked their core fans to madness — they still pull in tens of millions of users to the platform every month.

The company has lately been swinging in an entertainment direction — essentially, “use our platform to build characters you can play with Roblox-style, not companions you can talk to coffeehouse or sultry style.” Which makes sense given all those obstacles.

Such pivots raise a question we don’t tend to think about much but is unfolding before our eyes: which AI interface will we most be engaging with in the near future? Right now you regularly pop open any of a number of ChatGPT, Claude, Gemini, Perplexity, Copilot (and as of this week, OpenAI’s “Sol”). Or maybe you use none of these but imagine one day you will.

Wherever you fall on this spectrum, the question remains which we’re going to be using most and which will fall by the wayside. After all, this is the way of so many of our tech relationships — AltaVista and Yahoo eventually gave way to Google; MySpace and Friendster yielded to Facebook; Reels and Spotlight cower to TikTok, and on. A rolling stone gathers no moss, but a giant tech platform gets progressively bigger until it pancakes all the others.

With AI models, though, that doesn’t seem to be happening, at least not yet. And the question is: will it?

The answer goes to the core of our relationship with technology — in what ways it will most touch our lives and in what ways we’ll be holding it at bay. Each of these chatbots work differently and have a different specialty, so which one wins out will tell us something about what we want from all these ones and zeroes we carry around.

Anand had an interesting thought on the question: none will win out. Or, none will lose out. “I think you’re going to see a lot of different swim lanes,” he told me. “We’ll use each one for a specific job.”

He believes each of these specialties will in a way double and harden, so that we will no more use an unrelated one to solve our problem than we would a hardware store to buy groceries. You’re going to want to fix something? You’ll go to ChatGPT. You’ll want to code? You’ll use Claude. You’ll want to look up source material? Perplexity. You’ll want a bonkers answer to make you swear off all technology forever? Grok. You’ll want to know who to vote for? You’ll —wait, who does this? (Apparently more people than you think.) That’s Anand’s argument.

I’m not as sure that will be how this stuff shakes out. For one thing, tech companies rarely stay in their lane, even if it’s in their interest to do so — the nature of profit-generation compels otherwise. So we’re going to see a lot of these companies make some inroads in what are supposedly the specialties of other companies.

Also, while I believe it’s true that any given interface could be better at certain modes of inquiry — just inevitable, really, given the differences in training data — I’m not sure we’ll really see users cherrypicking that way. I think most people want convenience — that’s what a chatbot brings in the first place — so the idea of firing up new apps for different use cases seem like a bridge too annoying. Instead convergence (that one’s also for the OG’s) will abide; we’ll gravitate to one app, individually or societally, even for areas where others outperform it.

What Anand’s answer doesn’t get at is how we’ll use these chatbots for something that goes beyond a task — so far beyond it really has nothing to do the any kind of tangible result. We’ll use it to counsel us when we’re confused, to cheer us up when we’re down, to accompany us when we’re alone. We’ll use it to feel like a person is there when they’re not, or a better being is there when we don’t like the person who is. We’ll use it, really for feelings.

This can seem like….not science-fiction, but a little out of the realm of our experience. But of course it isn’t implausible — in fact it’s already happening. The most persuasive proof of which is that, well, character.ai has 20 million monthly users, and many of those people are not using the platform to find out information. Anand knows this, of course, and has a vested interest in steering us in another direction — the emotion-reliance model is what’s gotten the company in so much legal and regulatory trouble in the first place. But the reality is people have many emotional needs that humans can’t solve, therapy is expensive and only goes so far, and a form of intelligence is right there for the programming. And as a result can do what a search engine never could.

Now, in this realm it’s even harder to tell who will win. Mainly because most of these platforms I’ve cited are not explicitly optimizing for feelings; they’re about optimizing for tasks. But these systems are all about adaptability, and so I think we will lead them — either literally with training or indirectly with their owners’ profit motive — to places where that does become the default use-case. So I’m not even sure we know the app that will be our biggest go-to, because it’s hasn’t been invented yet, or if it has then not in the form that will ultimately be most popular. Like, maybe ChatGPT or Gemini or Claude ends up being our go-to AI friend. But I doubt it.

A new YouGov study found that for most Americans seeking information “Search engines remain the preferred starting point” compared to AI bots — only 16% of consumers prefer the latter. I couldn’t help laughing when I read this. The whole study presupposes that we will use AI bots for the same thing we use search engines — for a purpose it wasn’t designed. It’s a little like asking the hardware store if it carries milk. It doesn’t. But someone’s gonna build a killer bodega that does.

2. A LITTLE OVER A YEAR AGO WE INVESTIGATED THE FUTURE OF READING — that is, what does the idea of taking in text information mean in an era when there is so much of it produced (thanks to bots) and so many faster ways to consume it (thanks to bots).

The subject is now coming up again for multiple reasons, in part because a lot more text-based media companies believe video is what will draw consumers’ attention, in part because The Atlantic just ran a story whose headline, ahem, read: “The End of Reading Is Here: Optimists once believed that universal literacy was inevitable. Now it seems that the age of reading might be a short anomaly in human history.”

With all this noise, who has time to do any reading? Also, who needs to read when machines are getting so good at summarizing long books and large documents and spitting out cut-to-the-quick bullet points?

With this in mind I thought I’d revisit the piece from last year and excerpt the relevant parts. See what you think from the point of view of Summer 2026. But also remember how long reading’s end has been predicted, sacrificed on the altar of visual technology (”Fahrenheit 451,” e.g., more than 70 years ago), and how everything from longform to book clubs have risen in their wake. It may simply be that human beings like to process words and stories on a page. Anyway, our take on how this will all shake out:

What is the future of reading? I don’t mean that in a schoolmarmish scolding way, like kids today don’t read enough and what is the future of literature if Jane Eyre isn’t embraced like it was when I was your age?

I mean that in a very basic, bar-is-so-low-even-the-12th-man-on-the-Washington-Wizards-can-clear-it kind of way. As in the, the very act of reading: will it still exist when our grandkids are our age? Or, in, like, five years?

Last week I visited the Meta offices to get a glimpse at what its new Ray-Ban AI glasses could do. A lot, as it turns out. One of those things is read for us. You put on a pair of glasses, look at a block of text, and then hear an auto-generated voice in your ear telling you, in much more concise form, what’s on the page in front of you.

What the program is actually doing is combining several functions — capturing all the text with a camera, putting it through an image-to-word translator, using an LLM to synopsize those words, then using a multimodal program to read you that synopsis. But basically, it’s reading for us.

I should caution the tech is not quite there yet; the glasses only get a page’s most basic rudiments. But sitting through the demo I didn’t have to engage my imagination too hard to see a much different world than our own — one in which “reading” is little more than a quick stare at a page followed by a sweet summary in our ear.

For now, Meta is keeping the focus on something you either don’t want to read or don’t have time to read, like that museum blurb you just photographed you’ll absolutely return to once you’re home and off your feet. More critical applications also beckon — like medical information in a foreign language. If you’re in a hospital in Fes with suspected food poisoning, you don’t want a crash course in Darija. You just want to know how not to die. Meta Ray-Bans are here to help.

But these very specific inarguable use cases often bleed into more general-interest ones when the market and money arrive. I mean, the Internet was developed for the military. Reading summaries could easily go from hospital warnings to news sites, then to homework, to work email, to church bulletins and on. Pretty soon you’re putting on these glasses anytime you’ve got a book-club deadline. Colson Whitehead is great, but who has the time? Reading will be for the retired and the gullible. Why churn butter when a tub of Land o’ Lakes stares back at you from the supermarket aisle?

And we’ll absolutely see this in professional contexts, the AI reading where the person (employee) once did — the paralegal that once combed through case law, the Hollywood assistant slogging through spec scripts. It’s funny: we’ve focused so much on how ChatGPT and other programs can write for us, we’ve not much stopped to think whether it could read for us too. (Technically it’s actually a little harder, since the predictiveness element doesn’t apply. Still.)

“Your grandchildren will be the last generation to read and write. I think we’re at the dawn of a new era of AI-enabled communication,” said a tech executive named Victor Riparbelli in a recent Ted Talk, and while as the head of a video-based platform called Synthesia he’s hardly the most impartial person to make the case, he does offer a plausible argument for the ease of video and audio communication that, when combined with AI reading and writing, does inch us closer to that vestigial reality.

Now all this sounds suitably dystopian, and it is. We can deal with our brains forgetting how to puzzle out maps in the age of Waze. We can even deal with an AI scheduling our meetings or running our online errands, as it likely will soon do. But reading? Do we really want a machine doing that for us?

So allow me to go a little Yuval Harari on you for a second. I’m not sure this is reassuring. But it is...contextual.

For many centuries of course man didn’t read, first because writing wasn’t invented and then because publishing wasn’t invented. Movable type didn’t come around until the 15th century, and even in more educated societies about half of all people still didn’t know how to read at the start of the 19th century. That all changed over those 100 years, of course, and by the start of the 20th century most people in the developed world knew how to read.

Still, that means reading is hardly an innate human activity, historically or evolutionarily. The first man walked this earth around 2.8 million years ago, and for about 2.78 million of them most people didn’t scan their eyes across a bunch of characters to understand a set of meanings. Socrates actually didn’t think reading was that useful — in fact he thought it would make people lazy and erode memory; how hard did your brain have to work if you could put everything down for posterity?

That’s of course comical given what we now know about the importance of reading for memory and the human brain (and reminds how technology eventually proved beneficial is often initially feared). Yet recalling such Socratism it’s possible to see a future of human reading not as an inevitability but an uncertainty, insane as that sounds (and insane as it is to write knowing how you’ll consume this message). I mean, there are a lot of things we didn’t do for a long time, and it doesn’t mean we should go back to not doing them. But civilization was able to thrive and people could lead happy lives, so to assume that this is a skill that must be taught, practiced and cherished is to forget that history.

Now that we know, do we want to go backwards? Well, no. But humans militate toward the convenient, and if we can seemingly achieve the same effect while putting in a lot less labor we usually do it. Which makes me think the Meta glasses and their ilk will dramatically change our reading habits and abilities in the nearish future.

So where will that leave us? Evolutionary scientists simply have no recent fact pattern for the conscious abandonment of a skill like this. Reading has an incredibly beneficial effect on our brains and even our longevity, and what would it mean to let the muscle go flaccid?

Nor do social scientists know. It’s simply hard to decode a world so scrambled. Will reading in this AI-assisted age become a privilege only for the elite? Or could it be, head-spinningly, the opposite — only the POOR will be able to read because they can’t afford an AI to do it for them? This status stuff has a weird way of reversing. Corpulence used to be a sign of wealth. In the Ozempic age it’s the opposite.

There is one silver lining to an AI reading-program. Too much of our reading now, most of us feel in our souls, is done to no particular end. The average office worker receives 120 emails per day, and ten of them have the information we need. This didn’t have to be an email.

If some of our hours scanning text could be skipped thanks to an AI doing the grasping for us, does it free up our reading time for something more valuable, more pleasurable? That is, would we still spend the same amount of time in the day reading, just on the stuff we wanted to? Most of us can’t imagine ever giving up the joy of a “Harry Potter” or Stephen King or other literary property that lodges in our heart, and maybe now without all those emails to run our eyes over we’ll have more time for it.

That’s the optimistic view, anyway. And if there’s one thing reading all those self-help books have taught us, it’s to hold on to optimism.

3. FINALLY, IT’S BACK TO SCHOOL TIME.

OK not really, but you’d never guess it from the way school systems are panicking about AI for the September return.

In the New York City school system, the country’s largest, the chancellor Kamar Samuels this week told the principals of the system’s 1,800 schools not to buy any new edtech software for the moment.

“We know that we must prepare our children to thrive in a world increasingly shaped by new technology. We also recognize the need to consistently provide a safe, developmentally appropriate system with robust transparency and oversight,” went the email.

A nice assessment of competing needs. How to resolve that competition? Less clear.

Obviously “ed tech” is a broad category and runs the spectrum from lifesaving tools for struggling students to lazy cashgrabs that will ruin and addict young minds. We’ll take a look at products that populate various points on that spectrum as we get closer to the September return. But for now I just thought these two paragraphs in the Gothamist story today about Samuels’ letter said it all re where we are with AI in our schools, and generally.

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“In a speech in May, American Federation of Teachers president Randi Weingarten called for a ban on AI in elementary schools, and no chatbots for kids under 16. She also called for a screen ban in pre-K through second grade.

That represented a shift from the powerful union. Last year, the union opened an AI training center in Lower Manhattan in partnership with Microsoft, OpenAI and Anthropic.”

What a difference a year and no raised-scores make.

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? Last issue, we occupied positive territory for the fourth time in a row. This week? Not so much.

A CONFUSING MESS OF CHATBOTS: And some emotional-companions too -2.5

READING, IT STICKING AROUND? -3.5

EDTECH POLICY COULD USE A CRASH COURSE -1.5

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

-7.5

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

+4.5

Every Thursday we come at you with all the AI and future-world news you need to be informed. Join our journey.

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I’d neglected to mention last week, but I will this week, that I recently had the opportunity to chat on-air with the lovely Rachael Myrow from KQED, taking listener calls on AI, creativity and the future. Give a listen if you get a moment.

And speaking of creativity, this week for THR I also had the pleasure of talking to the leaders of OpenArt, a newish startup looking to bring AI tools to the creative world, including a directing tool that basically guides you from ideas to postproduction all through your laptop. They were delightful and interesting, and love or feel conflicted about what they’re doing, their energy is undeniable. You can check out our interview here.

An info-rich issue this week’s as we conduct our semi-annual report card/crystal ball on how AI and our techno-future year are shaping up. We’re coming to the halfway mark of 2026 in a few days, and there have been some storylines, man. From Anthropic’s dance with the Defense Department, to the AI bubble-burst that may finally be looming, to drug discovery that is legit mindblowing, it’s been a heady six months, and the back-end promises to be just as dramatic. We’ll break down what you need to know.

Also, last week we told you about the stakes of the Alex Bores Congressional election in New York. This week we got a result. More on all that and where the AI regulation movement goes from here as well.

First, the quote of the week:

“Future victories will be built on the progress of this campaign.”

—Alex Bores, sounding hopeful

Quick note o’ summer schedulin’ that we’ll be out next week for the Fourth (/Taylor Swift wedding), back the following week, out the week after, but then with you through much of the summer until a little well-earned break at the end of August. Weather’s hot and pool’s a’beckoning; why don’t you spend some time splashing around with us?

Also, this issue marks the completion of the third year of this here Substack. Woohoo! Thanks for being such an instrumental part of the journey; you guys are what make it all worthwhile.

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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

China, bubbles and drugs; Bores bows

1. SIX MONTHS INTO WHAT HAS ALREADY BEEN A DIZZYING YEAR WE WANTED TO take stock of what’s been happening on the AI front. So here are four storylines that have already been full of some wild turns, with no doubt plenty more to come.

AI and the Defense Department

How much should the U.S. military be using AI? How much should AI companies allow themselves to be used? The issue came to a head this winter when Anthropic wanted guardrails on what the Defense Department could use its products for, particularly regarding mass surveillance of U.S. citizens and autonomous weapons (said department wanted zero strings),

Anthropic pulled out of the deal, to no small amount of retributive swagger on the Defense Department’s part; the courts stopped that swagger dead in its tracks; but none of it really mattered anyway because OpenAI stepped in to offer its services. Their tools are not regarded as strongly effective but they still get the job done, which means the military got what it wanted and now has a wide range of tools to spy and sift through data as it sees fit.

Just a few weeks ago, the U.S. government ordered Anthropic to cut off access to its powerful Fable and Mythos models for all foreign nationals, a decision that left the company not the least bit pleased. The beat goes on.

Nor is this the endpoint of the military and AI. The Defense Department already relies heavily on Gemini, the Chief Digital and Artificial Intelligence Office has “unleashed” an “AI-first War Department” in which “Warfighters have the AI-enabled capabilities necessary to train, fight and win” (seriously, check out this almost comically over-the-top Web site), and the president earlier this month gave a 90-day timeline to defense and intelligence departments to “responsibly accelerate the use of AI” and rewrite an autonomous-weapons directive in a way that will surely increase its adoption.

The U.S. military is now going full roadrunner on AI, believing these tools and techniques can’t get adopted fast enough. (A Democratic senator from Arizona is trying to get transparency from the Pentagon on this process.) Will these systems actually make us safer? Or just become fodder for exploitation? The rest of 2026 will be fraught and revealing.

AI and the Bubble

We’ve been hearing about a bubble-burst for nearly a year now. The prediction template goes roughly like this:

Companies are spending nearly $600 billion annually on AI investment, and the stock market has risen 8x on the insatiable appetite for chips and other products associated with this speculative boom. When the speculation doesn’t materialize and demand plummets, the stocks that have benefited will crater, the AI bubble will pop and the economy will come crashing down in its wake. So goes the prediction. The losses are too great, the wealth too concentrated, the economy too lopsided and the hype too out of whack with the consumer utility for anything but a dark day to come.

Or as the tech journalist and author Cory Doctorow said in a speech several months ago, “When the AI investment mania halts, most of those models are going to disappear, because it just won’t be economical to keep the data-centers running...The collapse of the AI bubble is going to be ugly. Seven AI companies currently account for more than a third of the stock market, and they endlessly pass around the same $100b IOU….AI is the asbestos in the walls of our technological society, stuffed there with wild abandon by a finance sector and tech monopolists run amok. We will be excavating it for a generation or more.”

Jeremiah, perhaps. But Jeremiah was also mostly right. This week a sell-off on Tuesday brought the NASDAQ down 2%; overseas didn’t fare much better. Some individual tech stocks dropped double digit-percentages (a bit of rebounding happened since). Doctorow spoke to Arts Technica this week to promote his new nonfiction book “Reverse Centaur” (the title refers to a doom prophecy of humans being an appendage to the central AI body) and he decried the bubble and predicted its popping, while outside the interview walls that narrative inched forward.

“Imaginary markets have no agreed-upon valuation because you just made them up,” Doctorow said. “Unless you can turn an imaginary market into a real market pretty quickly, you need to come up with another imaginary market and announce that this is the new imaginary market you’re going to conquer. It’s easier than you’d think because the capital markets have the object permanence of a toddler, and they would lose a game of peekaboo if they were drafted to play in the league. So you can say, ‘Oh, actually, it’s not metaverse. It’s crypto. It’s not crypto. It’s Web3. It’s not Web3. It’s something else.’ And the markets will forgive you, provided you do it quickly enough.

“But something different happened with AI. It is much, much bigger in terms of capitalization than anything we’ve ever seen—not just bigger than other tech bubbles, bigger than other bubbles. When I wrote the book, capital expenditure (CapEx) globally was $700 billion, now it’s $1.4 trillion. Meta wasted $60 billion on the metaverse. They spent $150 billion in the last three years on AI, and they say they’re going to spend another $150 billion this year.”

Doctorow calls for a puncturing of the bubble (“pop it, as quickly as we can,” he said in the speech.) Which could cause plenty of pain. More desirable is a slow deflation, one that neuters the companies that both drive up costs in a fevered economy and use AI to justify the laying off of large swaths of workers — but doesn’t do it so fast it collapses the stock market and hundreds of millions of retirement accounts with it. A less easy trick, and one I’m not sure we could pull off. More likely Doctorow is right and the bubble keeps inflating until it pops, harshly. The next six months will tell.

AI and Medical Discoveries

Having given you the bleak realms, time to turn to a brighter one. The medical use cases for AI have been abundant for a while, and they just keep coming. This week we got another one: a paper in Nature in which AI (specifically deep learning) found a potential leading suspect in a common cause of death.

Some 350,000 people with few risk factors drop dead of sudden cardiac arrest in the U.S. every year, puzzling scientists. The machine found a correlation to cardiac fibrosis, aka a condition in which scar tissue is scattered throughout the heart. That’s something researchers could literally not have done, examining the echocardiograms of hundreds of thousands of people and cross-referencing them with death certificates, and the fact that machine-intelligence could uncover a culprit hiding in plain sight is straight-up nirvana.

Nor is this an idle finding: these deaths can be prevented with an implantable defibrillator. Before, we’d never put one into an empirically healthy person. Now, with this new risk factor uncovered? We just might, and save thousands of lives.

Such discoveries are hardly anomalous. AI recently combed through a huge library of 45 million anti-bacterial compounds — a painstaking and underfunded operation when researched the human way — to successfully find two potential new antibiotics with relative ease. And a paper in the Journal of the American Chemical Society earlier this month laid out how AI found a pocket in a protein that’s a target of cancer treatment that human researchers has missed, potentially allowing drugs to be more targeted and this more effective/less side effect-y.

The ability of machines to comb through so much data and spit out a result may seem like it’s coming to take a low-level job, or claiming designs on a higher-level job it can’t do all that well. But it also is coming to do a job no one can — and give us life and health in the process.

AI and the China Invasion

You know how American tech companies/libertarian politicians use competition from China as an excuse for a complete lack of regulatory oversight? Well, there is a complete lack of regulatory oversight — and China is surging anyway.

A head-spinning number of developments have unfolded just over the past few weeks, and they all favor the Middle Kingdom in the race to dominate AI.

First Microsoft said it was debating building Deepseek — that cheaper AI that back in the winter of 2025 sent shock waves through Silicon Valley — into Copilot, a potential major inroad for China into the U.S. market. Then came another Chinese startup model, Z.ai, which was swelling in popularity and giving the big American companies a run for their money. In fact, the latest rankings for most-used LLMs have Chinese-based products occupying all four of the top spots, unprecedented since the rankings started. Deepseek is so feeling the burn that it just announced it’s doubling staff.

The reason this is happening is not plain technological superiority — and it’s certainly not American regulation, as again, it’s non-existent. No, the main reasons China has suddenly gained an advantage is that they have figured out how to produce AI outputs cheaper, which means it’s cheaper for customers to buy. The country also (not unrelatedly) has kept nearly all its models open-source, which means others can iterate upon it, generally making products cheaper (and better). Silicon Valley firms won’t do that because it cuts into the money they make; if others can build off it they need you less.

Essentially what the Chinese companies have done is trade added profits for the few in exchange for power for the nation. That is a much harder road for an American capitalistic society to mandate, though companies could of course decide on their own to go open-source and counter this rise. (They won’t.) So here we are in a looming age of Chinese AI dominance.

What does this mean for you? Nothing. And everything. The nothing comes because it doesn’t really matter to individual customers where any tech product comes from as long as it’s appealing, and if you doubt that ask people how much they’ve given up TikTok to go all in on Reels.

But Chinese AI superiority also means an American weakening, never good for the economy or general national prospects. Plus the ongoing concerns of what Chinese AI companies could be feeding back into their national-security maw; all this is happening amid worries, for instance, that Anthropic has given access to its powerful/feared Mythos model to a South Korean company, SK Telecom, with ties to China.

On the other hand, if the bubble bursts, at least there will be fewer American giants collapsing under it. Silver linings.

2. FIRST, THE NEWS PART: ALEX BORES LOST.

The AI regulation hawk we told you about last week didn’t lose by a lot — about 4,000 votes out of ~100,000 votes tallied. But still, only good enough for second place behind veteran pol/operative Micah Lasher.

Now, the analysis part. Did Bores lose because of his harsh stance on AI, did his candidacy rise as a result of his harsh stance on AI, or did the issue have no effect at all?

The answer is yes.

First off, there’s no doubt he caught a wave. A 35-year-old Assembly member fairly new to politics running against a 44-year-old Assembly member who’s been in politics for 20 years (and had the backing of some of the biggest names in the state), well you don’t go toe to toe without some real heat on a popular issue. And Bores had that. People are worried about AI companies running unchecked, and Bores’ rise reflects that to a T.

Or as he put it in his concession speech, “Americans everywhere are seeing AI work its way into every aspect of their lives and their economy and they’re looking to see who will stand up for them.”

That said, many, many millions of dollars came in against him, from a super PAC underwritten by OpenAI, Palantir and a16z principals, and the commercials they blanketed the airwaves with, shameless as they were, seemed to have an effect. If the hopeful inference from Bores’ near-win is that a lot of voters vibed with his message, the not-so-hopeful inference from his narrow loss is that tech companies’ resistance to being regulated is even stronger than we thought, and they’re going to back up the Brinks truck to stop even one person who holds some basic common-sense ideas about putting up guardrails.

And finally, the no-effect factor. As much as AI regulation should be a major issue in political campaigns, it has yet to rise near the top of the list of Most Important Issues for voters, which means a candidate cannot ride it and it alone to victory, even in a pretty plugged-in place like Manhattan.

But that doesn’t mean it won’t change. As Bores noted, “Future victories will be built on the progress of this campaign; that’s how movements work.” Bores’ surge as a result of his AI platform has modeled an approach for many other candidates — for people in November contests and people in future contests and frankly even people already in office. Bores has taken an issue that a year ago most Americans would’ve shrugged off as a niche matter beyond their ken and turned it into something urgently relevant to them, to us. at the ballot box and beyond. In that sense, Bores’ candidacy is an indisputable triumph.

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? Last week, we occupied positive territory for the third consecutive week. This week? More good news.

AI-MILITARY ENGAGEMENT, AI CHINA DOMINANCE, AI BUBBLES BURSTING — BUT AT LEAST WE’LL LIVE LONGER: -2.5

ALEX BORES SETS A TEMPLATE: +3.5

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

+1.0

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

+12.0

Every Thursday we come at you with the crucials on AI and the future. Jump on our float. (And also, Knicks in Five.)

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This week, with the primary for New York’s Congressional District 12 just a few days away, we thought we’d take a look at what could be the most important (AI) election of our lifetimes. OK, admittedly that doesn’t cover a long span. But whether the candidate Alex Bores gets in or not on the Democratic side could spell a whole lot of difference on AI regulation, so all the noise and money expended for and against him — and there is a LOT of it — will have a real effect on where we end up.

And it’s not just a NY Democrat like Bores. A whole bunch of Republicans are ringing the same regulatory alarms — and from places where such a sound hasn’t been heard in a moon’s age. We’ll tell you about that too.

First, the future-world quote of the week:

“We are watching a handful of companies assemble a concentration of capital, information, and political power without precedent in the American experience. The covenant is being tested in real time, and we can already see the shape our fate will take if we do not act to reaffirm it.”

—Republican Senator Josh Hawley, in a jaw-dropper

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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

Don’t Bores, Get to the Chorus

1. UNAVOIDABLE THIS PRIMARY SEASON HAS BEEN THE CAMPAIGN, SUCH AS IT IS, OF KENNEDY SCION JACK SCHLOSSBERG.

Schlossberg has been held up as a textbook example of how tech can vault a political newbie, as the 33-year-old, despite his JFK grandparentage, has never held elected office but rode a surge of momentum with his troll-y social media to try to win the retiring Jerry Nadler’s current seat in CD12 anyway.

But a whole other tech dimension has played out for Schlossberg’s rival — Alex Bores, a state assembly member with a tech and engineering background. Who Bores is, what forces have arrayed against (and for) him and how the consequences of his win/defeat in the Democratic primary would play out are worth getting into, since there’s been a whole lot of smoke on the matter. We’re here, like a really strong beach towel, to wave away the haze.

You might be aware that Bores has pushed for some of the stiffest AI regulation around. Which isn’t that hard given the utter dearth of AI regulation in the United States at the moment. Still, the bill the 35-year-old proposed and eventually got passed into New York State law in December has genuine teeth — it requires that AI companies not just say they care about safety but publish and impose safety plans to prevent some of the more obvious harms. The law also requires more reporting on safety and other pitfalls to government authorities.

Now, the legislation — known as the RAISE Act — doesn’t deal with the more insidious harms of outsourcing our thinking and friendships to machines; it’s a step behind where we are with social media and the growing number of under-16 bans around the world. But it does put AI companies on notice and require more transparency and action on the doomer end of the consequence spectrum. It also normalizes the idea that AI companies are powerful products with all manner of safety risks we should take seriously and regulate, no different from a drug or weapon. A normalization that the current federal government refuses to engage in.

All of this has not sat well with these companies. OpenAI executives have stepped in to pour millions, via a Silicon Valley super PAC called Leading the Future (even its name is vaguely doublespeak-y), to take down Bores. They’re not advocating for an alternative candidate, just scrapping and begging so he doesn’t get elected.

Leading the Future is a pretty cozily SV-friendly operation; OpenAI president Greg Brockman, Palantir co-founder Joe Lonsdale and VC Marc Andreesen, an unholy trinity of eyebrow-raising technocapitalism if ever there was one, all fund it. Leading the Future is also a pretty shameless organization, tactically speaking, with how it tries to spin its way out of any government oversight — the old Giants Stadium did more astroturfing — and the ads they have taken out against Bores are almost startling in their bad-faith arguments. (Watch this one; the ratio of howlers-per-second is astonishing.) So a billionaire-funded pro-Big Tech group eager to stop any oversight of what they are doing, opposes Bores, which should make him more favorable right there.

But Leading the Future’s claims are also just absurd on their face. They spread the utterly laughable message that Bores is being puppeted by “dark money.” That allegation makes no sense — just because a rich person supports a safety-minded politician doesn’t mean there’s automatically conspiracy or puppeteering; by that logic only the impoverished can credibly support regulation. Of course they never say there’s a conspiracy, just insinuate one. Throw enough confusion at an issue, people get confused.

The super PAC also likes to point to Bores’ time at Palantir, but again, Palantir’s co-founder actually funds Leading the Future, so by their own logic why would that be such a problem? Also, people grow from their experience; if we stopped listening to anyone who worked at a problematic company we wouldn’t have whistleblowers.

And the doublespeaking lobbyists like to claim that the fight over Bores is just a fight between OpenAI and Anthropic — a matter of corporate rivalry, not fundamental safety — and so it doesn’t matter if you vote for Bores or not. The reason they can make this claim is because Anthropic and adjacent folks have in fact donated lots of money to Bores in the name of safety. But that doesn’t mean the company is up to the same special-interest influence game as OpenAI, nor that Bores wouldn’t have an impact in Congress anyway.

Readers of this space know what I think of Anthropic’s do-gooder efforts — basically, they’re one-third noble and two-thirds performativity. But whatever the ratio of that here, the result they’re pushing for would actually make a difference. It’s not like Bores can sponsor regulation that would carve out Anthropic. This isn’t pork-barreling — regs apply to everyone. And even the company’s motivation doesn’t seem that bad here. At worst you can say that Anthropic wants regulations the way Big Pharma wants the FDA — to build consumer trust in their product (and yes, hopefully looser regulation). But even a looser FDA is still better than no FDA, which is what OpenAI/Leading the Future wants.

The short conclusion here, and it’s really not that hard to come to, is if we care about even having a shot at government protecting us from trillion-dollar megaliths that will disrupt our labor, commandeer our decisionmaking and run our lives, we need more people like Alex Bores on Capitol Hill and a lot fewer tech-company rubberstampers, which is what Leading the Future is trying to smuggle in. ((I should note that Bores’ chief rival, Assembly member Micah Lasher, also supported RAISE, though has not made AI regulation as much of a centerpiece of his agenda.)

“No need for OSHA, we’ll just self-regulate our own factories,” Leading The Future argues. No thanks, we’ll go with some safety oversight. And more Alex Bores types.

Fortunately, they’re out there. Unexpectedly, they’re not all Democrats. Which brings me to the other half of this piece, namely: who ELSE in a position to make laws has AI Safety on their minds?

One big answer is: people in Florida. You wouldn’t expect regulation-allergic Ron DeSantis and his merry band of anti-regulationists in Tallahassee to be pushing for AI oversight. But that’s exactly what’s been happening.

Tom Leek, a Republican state senator from the northern coast of Florida, near St. Augustine, this past winter proposed an “AI Bill of Rights” that would, among other things, disclose periodically that a bot is just that. It would also prevent children from interacting with these bots without parental consent — commonsensical enough, not at all illegal now. (A tragic suicide of a Florida 14-year-old prompted this.) “There’s an inherent evilness when we allow machines to create and sustain a relationship that a user believes to be real,” Leek said at the time. “That evilness is only magnified when that machine interacts with a child or vulnerable adult.”

Now, the bill failed when it moved to the state’s house of representatives. But just the idea that a Republican elected would make bids like this is eye-catching right there. And it goes all the way to the top of the Sunshine pyramid, with DeSantis, as we told you a little bit about last month, this winter pushing that bill of rights, which also bans the unauthorized use of a person’s likeness and requires that AI companions share all their interactions with kids with said kids’ parents. All to go along with existing deepfake protections in the state.

DeSantis has not slowed down since, posting recently on President Trump’s push for a state ban on regulation that “Preempting states re: AI without enacting a sensible federal framework is just an amnesty for Big Tech,” while his AG just sued OpenAI for downplaying risks.

In a rational world, of course, these are all very common-sense moves. But we don’t live in a rational world. And we certainly don’t live in a regulatory world — not in DeSantis’ Florida. So the fact that he sees this as an, if not morally preferable, then at least politically expedient battleground to fight on tells you everything you know about the changing sentiment on AI protections, Leading the Future millions be damned.

But the coup de grace from a Republican politician on this issue was Josh Hawley’s essay last week in the religion-and-politics journal First Things. The conservative Missouri senator, you surely know, is no fan of government regulation as a general matter. But he has been staking out some serious populist ground on this subject, and the essay was the topper. I’ll just cite two passages:

“There are those, particularly in my party, who say we built the greatest and most prosperous economy in history by letting the free market and the gods of capitalism work their will. It simply is not so. We have chosen time and again to shape our economy, no less than our society, by the moral vision of liberty. We have chosen to put people before money. We have chosen to protect the working man as well as capital. We have chosen to shelter the poor.”

And:

“Left to itself, artificial intelligence will not choose moral liberty. It will choose the appetite. It will surpass the injustice of the Old World by gathering vastly more power into vanishingly fewer hands. That is the dissolution of the covenant. And it is the oldest temptation in the human story, dressed now in silicon.

Make no mistake: The barons of big tech have chosen their liberty. Listen to their talk of disruption, of moving fast and breaking things, of a world to be remade by whoever is bold enough to seize it. Strip away the jargon and you will find the same old creed: that might, in the end, makes right. That is not progress. That is the state of nature, the law of the jungle, scaled now to the cloud and bankrolled to the tune of trillions of dollars. It is the very thing John Winthrop and his band of Puritans crossed an ocean to escape.

In deciding how to govern this technology, we are not merely writing policy. We are renewing—or surrendering—the moral basis of our life together. The covenant does not keep itself. Every generation must swear it again. Ours will swear it, or break it, over artificial intelligence.

We do not have to imagine the stakes. We are watching a handful of companies assemble a concentration of capital, information, and political power without precedent in the American experience. The covenant is being tested in real time, and we can already see the shape our fate will take if we do not act to reaffirm it.

We’ll dive into the substance — an interesting faith-based-flavored argument against unchecked AI that dovetails snugly with the secular humanist position — in another issue. But just from a strategic/cultural perspective, Hawley’s political chess move here is fascinating, since he’s betting that the rising tide of AI labor disruption and safety challenges will be so great people will see this as a non-partisan issue. That is, he knows Democrats like Bores and California state senator Scott Wiener have made this a pet issue but doesn’t care, or doesn’t think voters will care. That’s a powerful statement about the potential for a bipartisan public groundswell on AI regulation.

Think about it: one of the country’s savvier politicians is now betting that people will care more about voting for officials who will do something to rein in tech than they do choosing their blue and red teams, the dominant motivational force in the political discourse for who-know-how-many years now. Hawley isn’t taking a crazy gamble; DeSantis and his AG aren’t taking a crazy gamble. They’re just gauging the weather.

As a result, this is all coalescing into what I think will be a bigger and bigger horseshoe in the next two years, such that by the 2028 presidential and Congressional elections we may well end up seeing a whole class of politicians from both parties get elected on a platform of robust protections against runaway tech companies.

Bores is the first test of this. If he wins we’ll know how voters — admittedly in one solidly Democratic (but still bougie and often moderate) Congressional district — think and how super PAC money from tech companies is no match for grassroots common sense. And it would inspire a lot of other potential candidates (never mind officials already in office) to take bigger swings on the issue.

And if Bores loses? Well, the good news is even then it won’t mark the end of a movement. It’s not like Lasher couldn’t push through some good AI Safety laws in his own right. In fact, Leading the Future hasn’t targeted him not because he’s so friendly to them but because they can’t well oppose BOTH leading candidates; that’s just a boneheaded waste of money even by Silicon Valley standards. And the very fact that Bores would have come this far, to a likely close second, will embolden other candidates and donors to line up behind the issue in future elections hoping it gives them a boost.

Bores is already a success story for anyone who cares about AI Safety and, come Tuesday, could be an even greater success story. The ballots should be in soon enough.

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? Last week, we occupied positive territory for the second consecutive week. This week? The good news continues.

ALEX BORES’ RISE COULD INSPIRE A WHOLE WAVE OF AI SAFETY-MINDED CANDIDATES: +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:

+11.0

Every week we try to make sense of this dizzying orb of technology and AI hurtling toward us. Join our rocket ship.

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This week I wanted to take a pause from the hurly-burly of the news to pull back and look at a big-picture issue, namely: when exactly should we use AI? Or, better, are we lumping too many use cases together and not drawing sharp enough distinctions between AI that could be very very good and AI that could be very very bad?

The answer is yes (or I wouldn’t have phrased it that way). In doing so we’re not just making it easier for tech companies that want to impose a dicey agenda to neutralize opposition with the Luddite label but also, in the other direction, we’re missing out on opportunities to benefit from AI by dragging the good down with the bad.

It’s a rich topic, and I’d like to offer what I hope is a handy and reliable way to separate between the categories, with an assist from South Park (!)

Since we’re riffing in this issue, I’ll forgo the quote of the week, but I hope you’ll find some good lines in the piece below. We all desperately need some lampposts on this dark twisty road ahead of us. Here’s hoping this provides just such high wattage, or at least a cluster of fireflies.

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IronSupplement

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

The Matt Stone Test

1. EVER SINCE I INTERVIEWED SOUTH PARK CREATOR MATT STONE THIS SPRING, I’VE BEEN THINKING A LOT ABOUT ONE LINE HE SAID.

Stone and his creative partner Trey Parker have been running a boutique AI studio called Deep Voodoo for going on seven years now, and it’s produced some of the coolest, most interesting and, to use a technical term, less slop-y creations out there. When I asked his larger philosophy about when AI and AI should and shouldn’t be used, Stone said this:

“I find that a lot of discussions about AI become tiresome. You know, ‘Put your taxes in and it can do them. And it’s like, ‘Cool, but a human can do your taxes.’ What we’re trying to do is something no amount of humans can do.”

Even when Stone said the line it made an impression, and I’ve found myself unable to forget it since, returning to it again and again in recent weeks. The creator was referring primarily to video generations, of course, articulating a philosophy about what kind of work the company would devote its energies to. Having Kendrick shapeshift, Donald Trump deepfaked or Bill Clinton de-aged are all the kinds of entertainment twists you couldn’t pull off with all the makeup in the world, so they were Deep Voodoo projects; creating digital stand-ins for locations or reconstructing a historical period are time-honored conventions that will work just fine if we have humans do them, so they weren’t.

But Stone’s comments turn out to be a surprisingly durable rule across the board, sliding easily in to so many realms: into scientific research, politics, education, medicine, legal work (and, yes, taxes and finances). In some cases we are simply trying to make some efficiency gain or not even that, just save a little money by dropping a machine into where humans were doing just fine. In such cases, Stone is saying he’s bored or even turned off by AI.

But drop it in to places where no human could possibly compete — in modeling drug experiments that would take decades and can now be done in months, saving countless lives, or in climate prediction where AI can tell us where a hurricane might strike and thus how to spend critical conservation resources — and now you have him excited. I use grandiose examples, but this can come down to something as granular as a risk for an individual patient or whether a hurricane will strike your house. In all of these cases, the model isn’t replacing the human — it’s one-upping the human. And we’d be silly not to take advantage.

Call it the Matt Stone Test: are we just trying to automate what’s already there or iterate what isn’t? Is AI an efficiency tool or an innovation? Tech companies like to say they’re all about “innovation,” but much of this doesn’t feel that way at all. Coding and graphic design, for instance, are two tasks humans do pretty well — we’ve had a lot of practice. Yet plenty of AI effort is channeled in these directions.

I’ve sometimes trotted out a distinction between professional use cases (eg, scientific discoveries) and consumer utilization, and that can map onto the Stone Test, but not always, and I think this is more exact. When it comes to the dividing line on whether AI is worth the cost — and there is a cost, in jobs, in the environment, in the general outsourcing of human thought and toil — it seems like whether an application can pass the Stone Test might be the best metric we can muster.

At its most elemental AI amounts to the scary-sounding but surprisingly simple idea: We shouldn’t be scared of what AI can do that we can’t. We should be annoyed when it’s trying to do what we can.

Now, obviously there are cases where the efficiency has a qualitative effect on the bottom line. Could the ability to shoot dozens of historical reconstructions make for better TV shows simply because we’ll have so many more? Perhaps. Even AI drug discovery works on this principal — the more you can look and the more quickly, the better the odds of finding cures. I recognize that the line between the same task done quicker and a new task done different isn’t always clear. Still it strikes me that enough applications fall clearly on one side of the line that we can use it as a determining rule.

What’s funny to me is that AI companies were once themselves all about this principle, and now either seem to be forgetting their roots or even actively muddling them.

The original mission for OpenAI was exactly this kind of sweeping, change-the-world philosophy. (You can still see the residue of this in Sam Altman’s pronouncements about super-intelligence and all the positive change it will bring to the world.) But somewhere along the way — possibly around the time they decided to become profitable — the company pivoted and entered the accountant-replacement business, which makes those Altman pronouncements seem either silly or hypocritical. The company became about selling the quickest tool to make our lives marginally improved for the sake of improve their margins. Yet was claiming otherwise.

Of course it’s not just OpenAI. Google DeepMind was all about moonshots and big ideas; now it’s a lot more about Gemini improving your ability to search. Anthropic wanted a more ethical version of OpenAI’s sweeping-hood; now it’s reveling in how well Claude can help you code. These are all cases of humans-doing-taxes. We have a system and it works, and instead of AI applied to new systems we’re just turning it loose on the host organism — on what humans already do well.

The problem isn’t just mission but messaging, or perhaps the messaging necessity. For years AI companies felt so pushed against the wall by critics saying they were trying to replace humans that they began underselling — they began saying they were “just a tool,” no different from a hammer or nail. But this was dumb, and anyone with their eyes half- open could see it was dumb, because a hammer and a nail don’t autonomously walk over and fix your dresser. What was more accurate — what they should have done to reassure people — is go the OTHER way, and say this was not a hammer or a nail at all, this was something entirely less recognizable and more magical. Had they focused on that idea — and showed how we really couldn’t live without these technologies as opposed to how these technologies make us feel like life is not worth living — we would be both infinitely better off and a lot less resistant, which is something you’d think the tech companies themselves want.

In short, we’re having the wrong argument. AI companies are trying to convince us they’re going under the human bar and not replacing us, when what they should be arguing (and doing, they key part) is vaulting OVER that bar and doing things no human could possibly conceive of. As ambitious as that would be, it would have the benefit of not actually replacing humans because no human is trying to predict drug impact or climate change at that level. But it would also have the benefit of not making humans feel like they’re being replaced since the whole rhetoric now would be about doing something that might help us.

Once we understand AI this way it will, I think, bring a lot more people to the responsible AI movement — people who intuit something is off here but have yet to discern it enough to pick up a placard — and get us collectively pushing for and against the right goals.

AI companies like to talk a game about building a complement to humans — some entity that will be smart enough to will help us but not so smart it will edge us into irrelevancy. But anyone can see that if this is your goal it will automatically lead to exactly what you fear, because the drive to make something more effective will naturally inevitably push us out; otherwise why would we use it in the first place? What they should be talking about (and, again, doing) is building an entire parallel infrastructure, not so much a complement as a new conduit, and focusing on the benefits of that.

This means fewer pieces of video and image slop, fewer inferior search engines, fewer AI Agents booking travel, fewer programs doing legal reviews, fewer use cases of AI as a shortcut to what humans were already doing fine taking the regular cut.* Fewer of those quick-profit plays, and more of those rewarding (and, I’d argue, ultimately financially enriching) humanity-advancing ones.

[*Not to mention deployments where it’s not just being used as a short cut for reputable endeavors but as a short cut for disreputable ones, like employee and citizen surveillance.]

This is why Eric Schmidt gets booed at college graduations. Not because anything technological is automatically bad. But because he has completely flubbed the Matt Stone Test while trying to pretend he hasn’t. He sees AI as something that is replacing your accountant but is trying to pretend it’s something that’s curing cancer. It’s sad when even a college senior who’s not yet in the work world can see through that elision.

I don’t know what the Matt Stone Test is realistic for publicly traded companies who see the “efficiency gains” (read: “replacing human-labor savings”) dancing in front of their eyeballs. When faced with two choices, the healthy and the heart-stopping, we know what tech companies reach for; that cardio-smart almond gets passed over for the dopamine hit of junk food every time. But man, this test is a good way to think about the issue. And clarify what AI is about — not at all bad itself, just unleashing some pretty awful effects when it’s cynically weaponized to make a buck.

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? Last week, we pushed into positive territory for the year for the first time — oh yeah. This week? More good news.

FINALLY, A SIMPLE WAY TO KNOW WHETHER AI IS WORTH PURSUING: +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:

+8.0

Every Thursday we come at you with what you need to know in the world of AI and future-news. Let this be your invitation to join us.

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We’ve got a slightly different format this week — shorter items, but three of them. Most important we didn’t want to leave you hanging on the biggest news: the Trump administration this week took its most decisive action yet on AI regulation. Does that mean the action is actually going to do anything? Well, that’s more complicated.

Also of note this week, you’re wondering how journalism is going to fare in the age of AI, when every piece of reporting gets put through a blender and no one know where anything comes from — and, oh yes, reporting can’t be monetized so reporters can’t be reporters anymore. NY Times publisher A.G. Sulzberger is worried too, and just gave a pretty stark speech about it.

Finally, you know how Elon Musk has his whole Neuralink brain-interface thing to help quadriplegics regain motor control? China may be beating him to it.

First, the future-world quote of the week:

“The companies driving A.I., already among the richest and most powerful in human history, are consolidating their outsize control over our data and our attention. At the same time, they are failing to embrace a core responsibility that comes with this power — to ensure the public has access to trustworthy news and information.”

—New York Times publisher A.G. Sulzberger, offering a truth that is fit to print

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IronSupplement

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

Trump the Regulator?; Sulzberger speaks; How China could cure paralysis

1. SO DONALD TRUMP IS SUDDENLY GOING TO REGULATE AI.

That was the quick headline, anyway, after the president in May first scheduled a signing of an executive order requiring companies to test new models, canceled said signing hours before it was to happen, then reinstated it on Tuesday, this time going through with the pen-stroke.

The very short takeaway is that opening sentence — the government can now review models to make sure they don’t pose undue risks. Woohoo! (The order has it that tech companies “provide the Federal Government with access to covered frontier models, subject to appropriate confidentiality, cybersecurity, insider-risk, and intellectual-property protection, use, and nondisclosure requirements.”)

The longer and more accurate takeaway is less simple. The government — via an “AI cybersecurity clearinghouse” led by the Treasury Department — only has 30 days to review the models (down from 90 days in the initial EO). The government has no discernible means of stopping the release of the models if they don’t like what they see. Oh, and even the initial review is completely voluntary on the part of AI companies.

Lest you have any doubt this was not meant as a very toothsome proposition, a social media post from the White House later in the day noted that “We are NOT conducting oversight of all new models, as that level of government overreach would have chilling effects on free speech and innovation.”

So the 1980’s EPA this is not. (More like the 2026 EPA.)

How many AI companies will participate, and how often, remains unclear. It’s possible some companies might look at the clearinghouse the way Big Pharma views the FDA — as a welcome branding tool to signal that what they’re doing is safe (even if they want the definition of safety to be…elastic). But it’s also possible that giant tech companies sidestep the process entirely. Move fast and break things has been the unofficial mantra for OpenAI and some of its competitors even long after the early Facebook motto became a parody of Silicon Valley recklessness. Just in the past few days the Sam Altman company has been handing out its software-vulnerability-finding (/hacking-in-the-wrong-hands) tool Cyber like candy to any bank that wants it.

Indeed, all this is coming as the tangible security risks — we’re not talking about slop or stunted social skills, serious as those are; we’re talking bioweapons and bank hacks — only grow by the day. Anthropic’s Claude Mythos is so potent the company yanked it at the last pre-release minute out of fear what it could unleash. But now they’re starting to hand it out more freely too.

So what does it mean that an EO has created a system in which some companies may or may not submit to a process that may or may not be able to do anything? That the approach complements a Congressional AI regulation bid that is unlikely to pack much of a punch (or pass) either? Certainly for a president who also has an executive order out urging states not to pass any AI regulation, it’s notable. But also a little like saying you’re buying a Diet Coke after eating a giant mound of cotton candy. There’s only so much it can do.

But if you want a little bit of optimism, here it is: the order does create an optics hurdle for AI companies — if you don’t submit, or if you do and the clearinghouse judges you poorly, and you release the model anyway, you’ll end up looking pretty bad if someone uses it to hack or otherwise harm Americans on a wide scale . Not to mention the symbolic shift: After nearly 18 months of nada, the president is at least recognizing the threat of unregulated accelerationist AI, or listening a little more to the members of his deeply divided Cabinet who are worried about it. Even if you don’t change your diet, at least you’re no longer pretending there’s no such thing as diabetes.

2. SOMETIMES A BREAKDOWN OF A SPEECH can’t hold a candle to seeing the original. Yes, even a human-led breakdown of a speech, no AI-summary programs in sight.

So it goes with New York Times publisher A.G. Sulzberger, who this week at an event called the World News Media Conference in Marseille unleashed a 40-minute barrage of truth bombs you simply have to experience.

You should, indeed, watch it in its entirety. But let us give you two extended snippets to provide a flavor of what he’s doing — in a phrase, speaking from a steel-man place of innovation about the social risks and ethical pitfalls of ripping off the hard work of journalists and just spewing it back to the world without no payment or sourcing.

First, on the downstream effects on journalism/democracy:

“How will A.I. change the news? How will those changes affect the information ecosystem that serves as the public square for engaged citizens worldwide? And what can the people in this room do to ensure the future of first-hand, fact-based reporting that’s essential to the health of our democracies?

The early signs offer reasons for us to be concerned.

“The companies driving A.I., already among the richest and most powerful in human history, are consolidating their outsize control over our data and our attention. At the same time, they are failing to embrace a core responsibility that comes with this power — to ensure the public has access to trustworthy news and information.”

Their hijacking of the public square is made possible by the original sin that animates their A.I. products — a brazen theft of intellectual property that has occurred at an unprecedented scale. Tech giants strip-mine news websites without permission or compensation. They repackage these stolen goods as their own, siphoning off the audiences and revenue that otherwise would go to the news organizations that created this work. And this happens not just once during the training process, but countless times every single day.

As a result, I fear we are careening toward a future with fewer and fewer journalists to do the expensive, difficult work of original reporting — going to places, talking to people, digging up information, covering important issues and events, providing context and analysis, investigating the powerful. A future where a crucial wellspring of a healthy society and a stable democracy — the truth, understanding and accountability provided by original journalism — continues to dry up.

This potential damage extends far beyond news. A.I. companies have raided civilization’s entire corpus of original works, an act that also poses a danger to the future of books, movies, music, research and an array of other fields. In the United States, these industries represent not just the heart of American cultural and intellectual life, but a pillar of its economy and one of its most powerful exports. Globally, creative professions employ over 50 million people worldwide who produce roughly $12 trillion of economic value a year.”

And then, to fend off the Luddite charge:

“Some tech leaders will portray my comments today as anti-AI. As defending the old status quo. As yet another ossified institution lashing out at the innovators who are driving the forward march of progress. And to be fair to our colleagues in Silicon Valley, there is a tradition of legacy incumbents — say a 175-year-old newspaper — complaining about new technologies and the disrupters behind them.

So it’s worth stating this plainly: The news organization I lead, The New York Times, has a long record of embracing technology to advance the mission of independent journalism. We have a history of respectful partnerships with tech companies to bring that journalism to new readers in new ways. Meeting disruptions with curiosity, openness and adaptability helped us navigate the collapse of our print business and come out stronger on the other side. Today my colleagues are using A.I. technology – responsibly, ethically, and with humans making the decisions – to improve how we report, edit, distribute and monetize our journalism. Holding a powerful new technology at arms length is a recipe for failure.

And I fully believe A.I. has the power to do a great deal of good in the world. I’m not calling A.I. — or the tech giants that control this technology — inherently bad or evil. I’m warning that A.I. companies are making choices that violate settled law, threaten the viability of creative work and appear likely to cause a great deal of unnecessary harm.

News organizations should want the good A.I. can bring. But tech companies should also want to support the healthy, sustainable flow of the information and ideas and creativity that powers A.I. — to ensure their actions don’t lead us to a tragedy of the civic commons.”

Ron Howard voiceover: “They don’t.” Or, more charitably, their instinct is generally to discount the survival threat to news outlets in favor of their own fast-cash monetization goal. Whether you use AI every day for every task under the sun or you wouldn’t get near it for all the crypto in Geneva, these issues should concern you. Precisely because it doesn’t concern them.

You can check out the full speech here.

3. YOU MAY HAVE BEEN FOLLOWING ELON MUSK’S NEURALINK, which for a number of years now has been putting into clinical trial brain-computer interfaces, or BCI’s, that allow people with serious spinal-cord injuries to regain some degree of motor control.

Basically the way the cutting-edge technology works is that a small quarter-size device sends threads into the the cortex, where it translates signals from a person’s thoughts and then sends it out either to a mechanical arm or back to a person’s own extremities that allow them to lift and control objects in a way they couldn’t with the connection disrupted. The idea is to apply it to a wide range of neural and other conditions that have led to limited functionality.

Musk has been pushing on this for years, though he’s not the first — a Utah-based company called Blackrock Neurotech has implanted their own BCI’s, using a less slick but equally effective tech, for about a decade now, before Musk jumped in and acted like he was the only one doing it. (He actually wasn’t doing it; UCSF scientists were, and he soon drove them so hard they actually left the company en masse, but another story).

Anyway, Musk’s claims of firstness vs a Blackrock already deep in was a rich irony. Because now a company has come along and lapped him.

The Chinese firm Neuracle has been testing a device called NEO that uses similar tech. A number of people have gotten it in their own version of clinical tials, including a Millennial named Dong Hui, as this story in MIT’s Technology Review notes. Dong was paralyzed in a car accident in 2018 but received a NEO two years ago and has seen moderate but thrilling successes, including the ability to write his name and pick up objects. (For an interview with a person who had gotten a Blackrock device, among the first in the world to have a BCI, check out one of the first issues of Mind and Iron from back in 2023.)

And now the big news: China has approved the devices beyond clinical trials — has allowed a commercial release that would (thoetrically) enable anyone who was eligible to go to their health-care provider and get the device implanted. (Also, it sits on a more surface part of the brain instead of at the cortex, so the procedure is less invasive.)

All of this still makes mass-availability very, very far off, of course, no matter whether it’s Musk, China or anyone else doing it. But wide-release BCI has been a kind of intangible dream for years, the tech yielding incredible hope and success at the trial level but seeming out of reach for ordinary patients. The very hard and long work of costs, distribution, insurance and other hurdles — never mind bringing it from China around the world — still remains. But with this bit of news we get just a little closer to taking one of the most devastating medical conditions and giving people a little hope.

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? Last week, for the first time in forever, we weren’t at a negative number for the year. This week continues the good vibes — we’re actually up.

DONALD TRUMP MOVES AN INCH ON AI REGULATION: +0.5

A.G. SULZBEGER GIVES A BANGER SPEECH: +2

CHINA IS MAKING BIG STRIDES ON BCIs: +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:

+6.0

Every Thursday we offer the finest (and not so finest)of what’s happening in AI and future-land. Please join our brigade.

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A crazy week just unfolded as the Pope spoke out on AI….and spoke and spoke. The 42,000-word Encyclical warning of needed protection for the human is like nothing the Church — or Silicon Valley — has ever seen. We’ll look quickly at what he did and then open up a new series: what do the world’s religions think of AI, kicking off today with the second-biggest, Islam.

Also, on our off week the Department of Commerce just, oh, nbd, handed out $2 billion in quantum computing grants to the likes of IBM (!), also taking a stake in the firms (!!). We’ll huddle up on what this means and revisit what quantum computing intends to do, should any of you have blissfully forgot.

First, the future-world quote of the week:

“So-called artificial intelligences do not undergo experiences, do not possess a body, do not feel joy or pain, do not mature through relationships and do not know from within what love, work, friendship or responsibility mean.”

—The Pope, offering the first but also kind of the mic-drop last word on AI

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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

The Pope and a Silicon Valley founder walk into a bar; Islam and AI; Q-Day?

1. BY NOW YOU SURELY HAVE HEARD, READ OR AT LEAST READ ABOUT (VIA AI) THE POPE’S ENCYCLICAL ON AI.

A more profound and surprising document you will not find — 42,000 words (longer than most Substacks!) of intermittent careful curiosity followed by repeated bursts of strong warning.

The most ardent lines you’ve likely heard as well, such as the spirituality-themed one from above about AI not possessing a body (a clear reference to those who would make it a God, I think) and the Biblical-themed one about the Tower of Babel. (“With the heart of a shepherd and a father, I ask everyone to abandon the construction of yet another Tower of Babel and to join forces in building up the common good, so that humanity will never lose its beauty.”)

That latter quote is sneakily powerful. The Tower of Babel was of course constructed by people in postdiluvian Genesis who got together and thought they could reach the sky; while a seeming testament to the power of collaboration (the builders all spoke the same language), it’s actually sideways shade at mass conformity: “If everyone thinks and talks the same, humanity will lose its specialness and society will fall prey to a flattening hubris.”

One hardly needs a divinity degree to see how AI can lead to exactly this. Once we rely on a machine weighted toward the average to think and communicate we’ll end up in that same flatland from where nothing good can emerge. (Plus the hubris part feels like a dig at the residents of Silicon Valley, who themselves believe they can reach the sky with superintelligence. In fact tell Old Testament readers from another age that this is what the 21st-century will bring and they’ll disbelievingly laugh and say “come on, no one is that on the nose”).

I asked a Vatican expert for a story in THR this week what he thought the Pope’s words could do in the real world — there are 1.4 billion Catholics, after all, and many of them are AI’s biggest customers — and the expert, a Fordham professor named David Gibson, said this:

“[E]verybody feels like a tsumani is hitting them but no one is really articulating why. And finally we have a world leader who’s articulating it in a powerfully coherent way. Who’s taking a lot about what’s turning over in our minds — about the threat of jobs lost, about creative destruction, about the destruction of the environment thanks to data centers.”

“People are hungry for action, for leadership, for a return to community and humanity,” he added. (Read the whole interview here.)

There’s a lot to what Gibson is saying. Until now we’ve had politicians (a disparate group, from Josh Hawley to Bernie Sanders) warning us to pump the brakes. We’ve had public figures in the creative fields (similarly disparate, from Guillermo del Toro to Scarlett Johansson) doing the same. Plus the academics and public figures, not least of whom is the man who invented AI himself (Geoffrey Hinton, as you know). But we haven’t had someone of Pope Leo’s stature or reach making the case. Now when Sam Altman drops blog posts in the middle of the night about how “AI will be the most powerful tool for expanding human capability and potential that anyone has ever seen….The world deserves huge amounts of AI and we must figure out how to make it happen,” he’ll be doing it against the backdrop of the Pope’s warnings.

Or now when all of us go download the latest tool, generate the latest video, or outsource a bit of research or decisionmaking we can use our brains for, we’ll remember Leo’s fatherly caution. Doesn’t mean we won’t do this stuff, but we may do it less, or different. Not to mention the tech executives themselves, who at least now in developing these products will have to contend with the optics, if not with a new moderating internal voice. tl; dr, I don’t think we can overstate the power of the Encyclical, from us everyday users down at the bottom of the food chain to the Silicon Valley alphas preparing the meal for us all.

Everything has felt a little chilly lately. The Pope just changed the weather.

2. ALL OF THIS TALK OF THE POPE AND AI, THOUGH, ALSO GOT US THINKING: If the leader of 1.4 billion Catholics could have this effect, what could leaders of a faith with an even bigger following — Islam — do to shape the thinking among their two billion adherents?

Or the clergy who guide the way for the world’s one billion Protestants? Or so many other religions, with their tens and hundreds of millions of followers — their novel ways of thinking, their time-tested dogma — that now must contend with this new, pseudo-spiritual force

This is all further amplified by a study I’ve always found remarkable. You’d think the people who believe in a Higher Power least would be most likely to believe in or use AI; they have a gap that this machine hivemind can step in to fill. While people of faith look to God more than a data set.

But it actually works the other way. A study a few years conducted by a Duke academic and a prominent Turkish professor found that those who contemplate the divine are more likely to accept what AI has to say. “Thinking about God promotes greater acceptance of Artificial intelligence-based recommendations,” they found. “Eight preregistered experiments reveal that when God is salient, people are more willing to consider AI-based recommendations than when God is not salient.” The skeptical forces that make people doubt religion also make them doubt the power of AI. And vice versa.

That means that the battle, if you will, over whether and how AI will be used will be fought heavily on the grounds of religion. At the global-pronouncement level, like this week’s Pope news, and in every house of worship and community. So it seems relevant to focus on the state of AI within different faiths at this moment.

Let’s take a quick look at Islam, following up with further religions in future episodes. (Requisite caveat that making any pronouncement about a faith is as silly as describing how a population feels about a food. Tastes, views and personalities vary; this is meant as general guidance.)

Islam and AI have begun to overlap in a number of areas, including the study of the Quran. Apps like Tarteel help translate and guide on Quran pronunciation, and they’ve become a key tool for people who want to increase their fluency in the text. Ditto chatbots generally for folks who find going to an imam too daunting or diving into the text too laborious. A chatbot, for better or worse, was meant for exactly this high-motivation, low-skill use case.

That has made some Muslim leaders optimistic about the tech. A Muslin AI ethics nonprofit leader named Waleed Kadous told Time this week, “If it's done correctly, it can really lead to people developing a better understanding of their faith.”

Of course there’s not much separating a lowered access barrier and a misinformation nadir. That’s what motivated Egypt’s governmental Islamic advisory and judiciary body back in January to ban the use of AI for any religious-guidance purpose. Tech execs might eyeroll such a move as centralized figures worried about diminishing their authority, but it hardly feels that simple. Knowledge of primary texts are declining across the population of many religions — this study about the plummeting rates of fluency in the New Testament is jaw-dropping — and leaders are justified in worrying that the use of chatbots will decrease it further. Because apart from the general dangers of disconnecting from primary sources, there are the specific dangers of AI hallucinating or being manipulated to give info about the Quran that simply isn’t accurate. Ease of access tends to come with less knowledge.

Of course when it comes to religion AI can post problems a lot more fundamental than just bad search queries. The idea of outsourcing thinking and decisions and even values is something many religions have a few ideas about, and Islam is no exception; Wadous warned in the Time article, as the magazine put it, “that major chatbots like ChatGPT or Claude reflect the values of their western builders, as much as they might strive for neutrality. ‘It’s very Western focused, it’s very individually focused, it doesn’t talk about community at all,’ Wadous said.” (The magazine also gave a rather startling example of a tradition-minded Gen Z-er who asked ChatGPT how to contend with the stares she was getting for a headscarf and the bot shockingly responded by encouraging her to take it of, something she was not looking to do, because it “doesn’t mean you’re a bad Muslim,” Reason No. 367 you shouldn’t use ChatGPT as an authority for anything.)

Maybe most important is that the idea of a superintelligent being would seem to conflict with bedrock notions of Islam and so many other religions about the supremacy of God. A verse in Quran 22:73 says that even if every person on earth gathered to create something “they will never create as much as a fly” compared to Allah. The Pope’s Tower of Babel warning, essentially.

Meanwhile, the Secretary-General of the moderate NGO known as the Muslim World League, at a major conference in Fez last month, called for an ethical framework around AI. Dr. Mohammed Al-Issa urged standards, transparency and guardrails, and honestly his call didn’t sound all that different from the Pope’s — or Hawley and Sanders — even if Silicon Valley executives might have bristled uncomfortably at much of it.

Islam lacks the central leadership of Catholicism, so expect more variance in how the tech is received; it will change by branch/sect, by geography, by community. But even with all these differences, caution and tentativeness rule the day. When it comes to embracing a technology that relieves us of thinking, Islam gives what we all feel: some appealing convenience, and some big caution flags.

3. ARE YOU READY FOR Q-DAY? You’re not? You don’t know what it is? You have enough to worry about without adding an alphabetical new concern?

Well, I’m here to tell you that you should worry (theoretically). Q-Day is when quantum computing — the idea of applying quantum mechanical theory to computing — comes into its own and essentially breaks the internet, exposing passwords, shattering encryption and generally creating mayhem. A sober but still eye-opening video in New Scientist this week laid out what could happen.

Of course, that presupposes quantum computing happens in the first place.

The reason quantum computing is on everyone’s mind is because just last week Commerce Secretary Howard Lutnick announced some $2 billion in new grants to IBM and either other (mostly smaller) companies to pursue more quantum computing research. IBM will get about $1 billion of it, and put another $1 billion of its own to create a quantum-computing subsidiary called Anderon. (The money comes from the Biden-era CHIPS Act.)

All nine recipients will give minority stakes to the government in return, which means on top of everything else the U.S. government now is part-owner of a potentially mega-powerful piece of tech.

Since some of you may still wonder what quantum computing actually is, we’ll surface part of a post we published last year on the matter. Not too much has changed — Google, Microsoft, Amazon and IBM are all motoring along. Except the first three didn’t take/get the government grant, no doubt not wanting to give a stake to the government. But here’s what you need to know.

Right now traditional computing uses data packets, which expresses language via bits that are either on or off, ones and zeroes — it’s literally a binary system. But with the help of quantum mechanics and subatomic particles, quantum computing’s “qubits” can be in both states at the same time. Which makes things go faster…a lot faster.

So strange is the power of qubits is that it cannot be apprehended — literally. The physics-based simultaneity of it means it can’t really be seen the way another object would. As a NY Times piece once famously noted, “If any of us actually looked at the fundamental building block of a quantum computer, called a qubit, it would cease to be a qubit.” (I know.)

The best (understandable) analogy I’ve heard for quantum computing vs the traditional kind is the requirement to move linearly across city blocks as opposed to passing through buildings with quasi-superhuman powers. Not only would you get where you’re going faster, but your whole way of moving would change.

Or, in this case, your whole method of computing. If quantum computing were to be achieved, you could (theoretically) solve problems no classic computer could. You could (theoretically) crack cryptographic codes and (theoretically) achieve new levels of drug-discovery breakthroughs, because you (theoretically) wouldn’t be bound by the same rules of computing. I say theoretically, because nobody knows what quantum computing can do, as it’s yet to be fully invented let alone tested. This is very experimental stuff.

What we do have are some promising intermediate steps to that steroidal end goal. That’s what Microsoft announced in early 2025. What they did was claim something called “topological qubits” that create those qubits by keeping materials in a state of matter that is neither solid, liquid nor gas, thus enabling that simultaneity. Again, very theoretical, as even some of the scientists who’ve been briefed on the research are only cautiously optimistic. But still, the kind of vista that even several years ago was hard to imagine.

In addition to Microsoft we also have Amazon’s first-ever quantum-chip prototype, an then of course IBM and Google too. Google in late 2024 announced its own chip, Willow, that could supposedly undertake a computation in five minutes what would take a traditional computer — wait for it — a septillion years to conquer. A Hollywood awards show will never be the same.

So clearly there’s an arms race. What happens when we get to the end of it? What will all this promise of speed and power mean for how we live? That’s a thornier question, and one on which we need to wait. (Possibly a while — while the developments are coming much faster in recent years, mainstream usage could still be a decade or more away.) But the idea, at least, is that quantum computing can power everything from batteries to AI, enabling a supersizing of the world we’re about to head into in such a way it changes not just quantitatively but qualitatively as well.

The nature of that quality is hard to predict. Yet clearly we’re heading there. Just five years ago Google made news by achieving so-called quantum supremacy after scientists there built a computer that took only about three minutes to solve a problem that would have taken a classic machine 10,000 years. Compared to the septillions of today, it was practically a Commodore 64.

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 bad. In fact after this week, we’re back to breakeven.

THE POPE JOINTS THE AI HUMANIST FIGHT: +4.5

ISLAM IS EQUIVOCAL ABOUT AI: +2

THE GOVERNMENT IS GOING DEEPER ON QUANTUM COMPUTING: -1.5

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

+5.0

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

0.0

Every Thursday we offer all the morsels you need to know on AI and the future. Please accompany us on our journey.

Subscribe now

This week I had the privilege of chatting with the fine folks at “Good Morning America” on what it meant for Demi Moore and a few other celebrities to (grudgingly) accept AI in art. The irrepressible Matthew Schaefer of the New York Islanders appeared on the same episode, and while I would have preferred that he talk about AI and I win the Calder, the current state of affairs is chill too.

In this issue, a couple of doozies. What the hell is the token tax, and should we care? A leading candidate for governor of California, Tom Steyer, is pushing this AI regulatory device. He told me this week why he likes it — how it can help ensure AI doesn’t run unchecked over our jobs and climate — and now you can decide for yourself whether you do too.

Also, if you’ve been wondering why you’ve been addicted to technology and only seem to be getting more drawn in, wonder no more: you’re actually the victim of a cruel game being played on your habenula, a part of your brain we’re only beginning to learn about. I talk to one of the country’s experts on how tech messes with it and how we can potentially unmess it.

Quick housekeep that we’re out next Thursday for the long Memorial Day weekend, back the following week with all the goods.

First, the future-world quote of the week:

“Our brain has never really been hacked before to make us feel intentionally bad about something so core to our selves.”

—Dr. Kyra Bobinet, researcher and health expert, on tech addiction

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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

Brain fry; Taxing the token

1. ANY OF US WHO PICK UP THE PHONE BEFORE BED TO CHECK ONE EMAIL, THEN FIND OURSELVES AN HOUR LATER SCROLLING THROUGH THE 183RD SOCIAL POST ON WHY THE WAR IN IRAN IS CAUSING A TOOTHPASTE SHORTAGE knows the feeling. Some kind of vortexy nether space has been entered, and it can’t be easily exited.

Ditto if you subconsciously reach for your phone when you wake up with your arm feeling empty without it; if you take out your phone when waiting for your friend to get back from the restaurant bathroom; and any one of 200 instances when a void seems eerily, upsettingly deep unless we fill it with some digital contact.

Many of us, recognizing this, wish we could do something to stop it — we get annoyed with ourselves that we can’t stop it — and yet go right on doing it. But we should be a little easier on ourselves: we’re not weak. We’re just being exploited by some very smart people who understand something about our brains and how to manipulate them, like the drug-dealer or fast-food marketer or that Svengali ex.

Dr. Kyra Bobinet has made a career out of explaining what that thing is — and, consequently, how we can level the field. A Stanford-educated health care executive and M.D., Bobinet has applied her research to focus on the part of the brain known as the habenula that regulates disappointment and need; it literally restricts your dopamine at a time of sadness. This restriction and our attempt to avoid it is, in short, what gets us into this addiction problem. (Some of these addiction themes came up in that penalizing Meta/YouTube legal ruling from March.)

A couple years back Bobinet wrote “Unstoppable Brain” to try to make sense of all this. We called her up so we could try to understand the tech addiction at this neural level (and also how we might get ourselves some methadone to escape). Here’s our conversation.

**

Mind and Iron: So let’s start with the habenula. What is it and why is it so important?

Kyra Bobinet: First, let me say the research has exploded only in the last 10 years. We had a delayed discovery period because we didn’t have an MRI that could spot the habenula until the 20-teens; it’s a half-centimeter, so you really can’t spot it with normal MRI machines. So this is all very new. Things like mood, depression, fear, fight-or-flight responses — we had been attributing so much to other brain areas. But now that we know what the habenula does, the research is exploding on just how powerful it is over all of our behavior, all of our mood, all of our choices, pain, stress, hunger, sleep, circadian rhythm, all of it.

M&I: And that includes how technology is in turn affecting the habenula.

KB: Yes, because when we’re avoiding certain feelings on our phone, we activate it, and that causes motivation loss, addiction, depression, anxiety, all of those really nasty side effects.

M&I: You describe the habenula in your writing as a “motivational kill switch.” How does that work?

KB: So anytime you expect something good, and you don’t get it, but also when you expect something bad, and you do get it, you trigger this area of your brain: This part of the brain that restricts dopamine in response, and then then what happens is that it kills your motivation to keep trying whatever you’re trying. Then secondarily, we notice, hey, I’m not doing what I should be doing in life, and we become depressed or anxious. And that triggers it again. So then it gets you in this loop where one bad experience leads to motivation loss, which leads to a lot more bad experiences, which leads us to more motivation loss. And it’s not just that we have the craving and we don’t get it. We’re actively trying to avoid withdrawal from the dopamine, so the habenula activates to try to prevent us from getting the dopamine — to prevent the withdrawal.

M&I: Wow, that’s such a fascinating, layered idea, that we’re not just needing, say, the likes on our post, but trying to regulate it so that we don’t need the likes, and that itself gets us into a whole world of trouble.

KB: There was research that I did at Stanford in the behavior-design lab where we found that the number one emotion coming from the unconscious was not to get approval but the need to avoid rejection. Our brain is twice as sensitive to negativity as to positivity. That’s what turns conventional addiction on its head, because we are more animals chasing after not having negative experiences than having positive experiences.

M&I: I’m reminded a little bit of, I think it’s LeBron James, but other pro athletes have said it as well, that he is motivated more by fear of losing than love of winning. That their motivation isn’t the joy, it’s to avoid the pain. It sounds like there’s a real biological basis for that.

KB: Absolutely, and that was proven by the Nobel Prize in science and behavioral economics went to Kahneman, who proved that loss was twice as potent as gain in our motivating behavior. And that just goes right back to the neural correlate of the habenula, putting the hurt on us. The anti-reward system is more powerful than the reward system itself.

M&I: The habenula serves a biological role, though, right: it protects us from making bad decisions?

KB: Yes. The problem is when for one reason or another — like a technology addiction, which we can get into — is it gets sent into haywire mode.

M&I: Let’s pivot to that. Thinking about this in the context of doomscrolling the whole equation starts to click into place. You’re looking for something, let’s say an article or a video or whatever it is we’re trying to find — something, we’ll know it when we see it. And we’re already a little addicted when we start looking — that’s the seeking of the positive, as it were. But finding it you’re saying causes this habenula activation — we’re disappointed we’re no longer looking; we have the crash from the withdrawal of the dopamine. And so we want to avoid that — we want to avoid the disappointment, as it were. So the minute we find it we start looking again, and that’s how we get into an infinite scroll.

KB: Yes that’s the mechanism; you described it perfectly. You’re compelled to keep looking because once you find it you have this crash and you don’t want that so you’re trying to get out of it.

M&I: Is this something that social-media companies are doing that no one else previously did in the history of marketing? Like, did Big Tech really invent this? I’m thinking how fast-food ads decades ago started working on our mental processes to feel like we’re never getting enough too. Madison Avenue in general from its earliest days has played on this kind of deprivation to keep us hooked. But we don’t see that as addictive. What’s different?

KB: It’s true, the ad agencies have been doing something like this for a long time — it was Freud’s son, I believe, who came up with the angst of you’re-never-good-enough advertising in the ‘50’s. This same idea: the pain of losing or feeling bad was so great you had to keep looking or shopping or whatever it is so you wouldn’t feel it. And once that precedent was set, once that was a mental model, it just kept getting scaled, until it’s just a click away and we can put the whole process on steroids with something that is constantly refreshing and targeting us with algorithms. So it just kind of snowballed on itself. I was fortunate to be at Stanford just post-Instagram; Google was just starting to get into applied behavioral science. And apps were pretty new. So there was a lot of synergy at Stanford Behavior Design with these kind of unlocks that really accelerated it. And a lot of the students from Stanford who were working on those experiments were hired, snatched up really quickly by Google and Facebook.

M&I: And what they figured out was that it not only was the techniques that were so addictive, but what we’re being addicted with, yes? Not just regular old products but all kinds of emotions.

KB: Exactly. They hacked a lot of things, like tribalism. The habenula on its own is healthy; it gives us a terrible feeling so we don’t make the mistake again. But it’s never really been hacked before to make us feel intentionally bad about something so core to our selves. The identity of a person is at play here. And that’s something that isn’t at play with an ad. An ad can come and go; you can kind of hold your breath for 30 seconds if you’re watching a Super Bowl ad or whatever, and then you’ll forget about it; your habenula doesn’t usually get activated. But the fact that they were able to leverage your social network and people you knew and your family and all these things you cared about and make it cohort-based. And then on top of that, target your specific psychology and what your particular vulnerabilities are. That was new. I mean, that’s what sports betting is doing right? They’re figuring out what the vulnerabilities are, where somebody’s habenula will give chase to a particular withdrawal of a reward, so that the addiction is perpetuated.

M&I: It’s the people at a slot machine mechanistically pulling the lever to avoid that withdrawal, only with much higher stakes.

KB: Yes, it’s not just the withdrawal of a monetary win, it’s the withdrawal of the win of social status, social standing, everything so primal to us.

M&I: I hesitate to ask how this can be turned off. Because if it is that primal, and tech companies have found a way to manipulate it, then what can we do to stop it once we let apps and digital culture into our lives? How do we stop our own habenula from being activated against us?

KB: So the habenula is turned off by only two hormones that we know of. One is melatonin, so going to sleep, and only, of course, when you can do that. And then the other one is GLP-1, which is a daughter molecule of oxytocin, which is a bonding hormone. And we need a lot more research on whether we should be using it to fight social media or really any kind of addiction.

M&I: I was going to say, should or will we get to a place where people come to their doctors and say “I have an Instagram addiction” and they prescribe GLP-1?

KB: I’m a proponent of short term GLP-1 in a case where you have somebody in a really bad loop with their habenula, whatever the reason. Because it then starts to collapse on itself, bad experiences killing your motivation leading to more bad experiences and then killing your motivation and eventually you’re suicidal. In those cases we just have to stick a wheel in the spokes to stop it. I don’t know yet how we should view GLP-1 in terms of the kinds of social-media addiction a lot of us have, which can obviously make us depressed and anxious and kill our motivation but — hopefully — doesn’t bring us all to that low a place. But maybe that will be where we end up.

M&I: The other option, instead of finding pills to break our addiction, is to get rid of the drug dealers: to recognize what they’re doing and try to stop it culturally or legally or legislatively, which we see now with the flip-phone movement or the Meta suit or the growing popularity of social-media bans at least for people under 16.

KB: That’s a very powerful tool as well and something we have precedent for. Just because someone designs an addictive product doesn’t mean we have to let them sell it everywhere. Look at tobacco, or the opioid crisis. Once it started to come out how out of control the crisis was, how we were being manipulated and people were dying, there were legal remedies, and the brand tanked, so to speak, and it became fringe.

M&I: I guess that’s the hope, though it took such a huge toll before we got there and of course it continues to take a toll.

KB: Yes, but then we come on to what we know as the implicit-memory system. That’s the idea where our subconscious registers something is bad for us and we start avoiding it, avoiding the addiction in the first place, even before we know we need to. There have been all kinds of experiments with this; Malcolm Gladwell documented it in “Blink,” where people would be given a choice between cards and one would always give them a better outcome of some kind and one a worse outcome and pretty soon they would start choosing that card that was better for them before they even knew why. I think that we will eventually get there with social media too.

M&I: One last thing before I let you go: the AI of it all. These social apps will soon be complemented with AI agents and friends and bots that cater to us — our digital time I think could be spent even more with them than with social-media apps connecting us to other people. Does the habenula manipulation exist at the same level of risk there? Is it bigger? It feels like because we can program the level of validation to what we need we might get even more addicted to it.

KB: From what we’ve seen so far I think the manipulations are not there yet. AI can still make us feel good and give us that withdrawal if we don’t get it, but we recognize these things as bots, and it’s just not the same level of addictiveness as the social validation we get from other people. We are likely to turn it off sooner. But I do think some people who are very emotionally vulnerable will remain in that kind of relationship with AI and it will be very addictive for them.

M&I: Which we’re already starting to see.

KB: For sure. And it can do damage. Right now though its manipulations are pretty simple. But that can always change, and the Turing Test can become easier to pass, and then I do see AI as a force that might play on our habenula the same way.

M&I: Something to look forward to!

KB: Yes, but remember the implicit-memory idea. It doesn’t mean we don’t have to try hard to push back. But our brain does tell us what’s not working for us. We just have to listen to it.

**

2. ALL KINDS OF REMEDIES ARE STARTING TO BE GET PROPOSED to counter AI companies that dislocate the human worker/mind.

We’ve told you a bit and then a bit more about the “robot tax,” the idea that U.S. companies should pay a penalty for automating work formerly done by humans, just like they’re, well, paying a penalty for exporting labor done by Americans, and we’ll continue to examine different kinds of solutions in the months ahead.

But raising corporate taxes is, for some reason (cough giant lobbying firms cough) difficult to pull off. Consumption taxes are, paradoxically, a little bit easier. That’s what the progressive California gubernatorial candidate Tom Steyer wants: to tax people for deploying AI both as a way to regulate its use and generate cash for the displaced.

I talked with Steyer for a story in THR about his plan to save Hollywood; you can check that out here. Over the course of that conversation he also mentioned the “token tax,” which is essentially this aforesaid idea of a consumption tax. “You want to use AI to generate media (ie, tokens), you pay a little extra for what you use.” AI generations according to this view are utilities, like electricity (not least because they use a lot of it), and as citizens in a resource-limited earthly realm, we pay for utilities.

Or think of it as a sales tax for the AI Age, maybe with an even slight moral dimension: you want to consume something that contributes to the degradation of the environment and the dislocation of the American worker, fine. But you have to give a little something back. Here’s how Steyer put it:

“We need to make sure we're protecting workers, and we need to own part of AI. And so we need to get the way, the best way to own it, to get a token tax, you know, a fee for every calculation, so that we can make sure that that money goes to protecting workers first and foremost.”

The idea is actually twofold: you’re obviously getting money as a government that can be given back to a displaced worker. But you’re also of course moderating the use of AI. People think twice before they buy something that comes with a surcharge, and so the net effect is to just slow the growth of AI companies, which would presumably also slow the pace of dislocation.

Policy experts are divided on what effects this will have — unintended ones are certainly possible, as they often are with new programs in new industries. Some seek to split the atom — a Brookings Institution study earlier this year made a distinction between consumer and enterprise use. “Token taxes on AI-generated content function as consumption taxes when applied to final users,” researchers wrote. “A fee per thousand words or images generated makes economic sense for consumer applications. However, such taxes must be oriented at the retail level—like current sales taxes—and exempt business-to-business transactions to avoid cascading effects that would make AI products less competitive. The goal is to capture revenue without creating barriers to AI adoption in production processes.”

I’m not sure I entirely agree with that — if the goal after all is to slow down these companies, why is it gospel we can’t slow down their B2B revenue too?

I’m also not sure if a consumer token tax will pass. People generally don’t like new sales taxes, though unlike an income (or even a corporate) tax, consumption levies do offer the pleasing benefit of not imposing themselves on you — you don’t want to pay it, don’t buy the item.

The trick with a token tax is to pass it now, before people are too dependent on AI. Because Big Tech will lobby against it, harder than Amazon lobbied against sales taxes bitd. In that case the company had an ally in consumers, who were becoming more dependent on the retailer and didn’t want to pay taxes either, and it was a long slog before the company was forced to collect taxes, harming plenty of critical public services in the process.

But most folks are not dependent on AI now — it’s generally seen as a nice-to-have more than a must-have — and I suspect a new tax on generating images or music will less produce an outcry than just cause a curbing of generations. (Less slop! Another benefit.)

And while I hardly think tech companies will be rushing headlong to accept a token tax, they might be slightly less resistant to this form of taxation if one had to happen; forced to choose between a robot tax and a token tax, they’ll probably choose a token tax because it doesn’t come directly from their coffers.

So in this sense I think it’s worth taking Steyer seriously, to a point: we should be piloting token taxes in some localities or states and seeing how they work — how they change behavior, how they generate income, heck even if it makes tech companies stop releasing new generative models or building new data centers every other Tuesday. None of such beta tests will stifle “innovation.” And they just might offer us a more slowed-down, human transition to the AI takeover of labor and empty tracts of land.

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 bad. This week? Eh.

TECH COMPANIES HAVE HACKED OUR BRAINS: -4.5

A POSSIBLE WAY OUT OF THE AI DISLOCATION ISSUE: +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:

+5.0

Every week we tell you what matters in the world of tech and AI. Jump aboard.

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We’ve got a slightly quicker episode for you today, but an important one still. It deals with two newsy questions: is the Trump administration actually coming to its senses on AI? And, relatedly, is there any hope for our future? It was a big week in regulation-land, and we break it all down.

First, the future-world quote of the week:

“There’s a lot of things that I’m excited about with respect to technology. Some of the things you can do with defense and robotics, and medical research, and things like that. But a lot of the power that it is being used is for consumer-facing slop.”

—A mystery speaker whose identity you will be surprised to learn!

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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

Start him up, he’ll never stop

1. LET’S BEGIN WITH THE QUESTION AT THE TOP, ABOUT WHETHER THE TRUMP WHITE HOUSE WOULD REALLY SEEK TO REGULATE AI. BECAUSE FOR A MINUTE THIS WEEK IT SEEMED LIKE THEY WOULD.

Then it seemed like they wouldn’t, then it seemed like maybe they were just saying they wouldn’t but really would

First, the background. For the past 16 months Donald Trump, no doubt swayed by the very generous fealty paid by Sam Altman, Sundar Pichai and other tech executives, has said no AI regulation. He said it with an executive order repealing the modest efforts of the Biden administration (which included requiring any company developing models more powerful than the existing ones run safety tests and inform the government what they found).

He said it with his own “action plan” last July that basically espouses, in a lot more words, “Tech companies, do your thing.” He even has tried to stop states from regulating AI — a constitutionally questionable move, never mind the ethics and pragmatics — though many states have openly ignored that call.

But this week, a turnaround for Trump. Several weeks after Anthropic said it wouldn’t release its new Claude Mythos model because it was simply too powerful and unbridled — mostly with finding weaknesses in the world’s most popular software systems — Politico reported on Tuesday that “the Trump administration is considering a slate of executive actions to address escalating security risks from advanced artificial intelligence models.” It then went on to suggest a potential “executive order creating a vetting regime that would review the impact of frontier AI models.”

This sounds an awful lot like the very FDA that Trump’s HHS Secretary presently seeks to gut. Heck, it sounds a lot like the Biden plan to require tech companies to report new models to the government. Heck, it sounds a lot more restrictive than the Biden plan since it would actually proactively regulate the models instead of just hearing about them by the by.

Lest you wonder if that FDA talk is an exaggeration, Trump’s own director of the White House National Economic Council, Kevin Hassett, went on Fox Business Wednesday to say that “We’re studying possibly an executive order to give a clear roadmap to everybody about how this is gonna go, and how future AIs that also potentially create vulnerabilities should go through a process, so that they’re released into the wild after they’ve been proven safe, just like an FDA drug.”

Sure, it wasn’t quite Alex Bores’ landmark bill injecting government into every step of the process. But it suggested a robust regulatory role for model-testing, effectively allowing the government to make sure a new system is safe before it’s unleashed on the public, and that seemed like an awfully big turnaround.

Then, Wednesday evening, a turnaround to the turnaround! With everyone in Silicon Valley and everyone in activist-land panicking/relishing, WH Chief of Staff Susie Wiles tweeted this: “The White House will continue to lead an America First effort that empowers America’s great innovators, not bureaucracy, to drive safe deployment of powerful technologies while keeping America safe.” (So much safe.) Another official told Politico that regulation was not on the table — “there’s one or two people who are very intent on government regulations, but they’re sort of the minority of the bunch.” And the walkback was complete.

So what’s going on here? Was the initial leak of a major regulatory action just the stratagem of a leverage-seeking squeaky wheel, and Wiles and this anonymous source a setting of the LP back to where it belonged? Or was there in fact about to be a big action, but after it leaked, the president, worried about spooking Big Tech and the large anti-regulator slice of the GOP base, had to (at least temporarily) walk it back?

In short, which was the administration’s view and which was political camouflage?

I’d like to suggest a third possibility: an administration that doesn’t know what it wants. I don’t mean that as a knock against the administration — no one knows what they want on AI. It seems entirely possible there really are two competing equal factions, with no Trumpian consensus, and this leak and walkback is just the surfacing of that divide.

In fact, I’ll go even further: I think what’s really going on is a battle between two values the contemporary Republican party holds dear. Between THE two values the contemporary Republican party holds dear — between the blocking of regulation that would hinder Big Business and a veneration of national security at all costs. Normally these can coexist, because what does business regulation have to do with the CIA.

But if Big Tech’s AI can really become so powerful, then suddenly Big Business becomes a national security risk. And suddenly the regulation so loathed with the first value is needed to uphold the second one. Let’s not forget what started all this: Anthropic’s Claude Mythos, aka the latest product from a company whose whole power lies in what it can do for the military. If even it was saying that what it had created was too powerful — ie a security risk — then shouldn’t the government listen, and regulate?

Which leaves us with a juicy question: how will this end up? Well, with this administration, who knows. But if I had to bet I’d say we land much more in Wiles territory: in some performative head-feint toward doing something that is really just talk of “collaboration” and “innovation” and in which government doesn’t end up overseeing AI at all, leaving it to the tech companies to do whatever they want — “self-regulate,” in doublespeakese.

But — and hear me out on this — I think any of us who feel government should actively step in to watch the tech companies will have the last laugh. And it’s not despite Trump’s inaction — it’s because of it.

Let’s unpack what the chain of consequences will be here. The Trump administration, in all likelihood, does little. The models keep coming. Sometimes an Anthropic stops itself — there are plenty of P.R. benefits to doing so too, after all — but more often than not AI companies release the models. (OpenAI but not just OpenAI.) That’s why they spend the billions researching them, after all.

So with all these new models come all these new use cases. Some are good, some are harmless and some, inevitably, are dangerous. They’re dangerous possibly because someone uses them to stage an attack on critical resources, as Anthropic worried about with Mythos, but they don’t have to be terrorist-level bad to be dangerous. They can also just cause mass job disruptions, or psychosis at a new level, or rob us of sound decisionmaking — point is, they’ll do something that people can feel and, probably, don’t like. So now you don’t simply have Donald Trump doing his anti-regulation Donald Trump thing — now you have horrible consequences his name is attached to because he had a chance to stop them and didn’t. Now you have all those Senators and the Iraq War.

And what does that in turn do? It opens up territory for a whole new group of leaders to define themselves against that Trumpian inaction by taking action. So now Trump has done a lot more than just look the other way on AI regulation as yes-men nod along — now he’s inadvertently created a whole new class of anti-AI activist politician. An opening and an incentive structure for a lot of politicians — even and especially Republicans — to define themselves by how much they will do on AI. (By the way it’s likely climate change will, for all the current administration’s bluster and harm, boomerang back too; it just will happen slower because the effects won’t be as palpably seen.)

The reason to think this anti-AI politician movement will happen is because it’s already happening. That quote above, about how a lot of what AI is being used for is consumer-facing slop? It comes from none other than Florida governor Ron DeSantis, who said that this week as he made a (for now) unsuccessful legislative bid to stop consumers from being harmed by AI.

DeSantis is hardly some regulation hawk — he just blocked a carbon tax and continued his anti-DEI witchhunt. But even someone like him sees the political opportunity on slowing down AI. You can bet there’ll be a lot more where he came from as the detrimental effects come into view, possibly in 2026 races and certainly in 2028. It’s a simple cause and effect — the tangible harms invite politicians to campaign on anti-AI promises, then enact them once in office.

Of course one would rather it never got to this point; regulation doesn’t have to kick in only when thousands get sick from PCBs But given that Trump is likely going to let the dumping continue, this electoral backlash could end up the best possible outcome. A toothless response on regulation just might be the best thing to happen to regulation.

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 bad. This week? Pretty good.

MIXED MESSAGES ON AI REGULATION BUT IT’LL WORK OUT: +3.5

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

+3.5

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

+7.0

Every week we bring you the most important AI and future-world news from a humanist perspective. Hop aboard our train.

Subscribe now

We’re coming at you a little later this week — early Friday instead of late Thursday — because I wanted to include The Hollywood Reporter’s The AI Issue which went up this morning. I, my friend and co-editor Julian Sancton and all our colleagues at THR have spent the past two months working on the issue. It’s a pretty comprehensive look at the future of entertainment from many angles — cultural, industry, you name it — and I hope you’ll take a moment to page through. There’s truly something for everyone. You can find the entire collection of stories here.

So we did end up taking that break last week, as promised/threatened. Hope you didn’t miss us too much. Plenty of news has unfolded in the interim. I wanted to focus this week on a couple developments/stories that tie into a single theme. Basically:

AI is coming to automate _____ [profession], we should feel ____ [adjective] and we should react by ____ [verb with object]. (Do you remember Mad Libs? Mad Libs were awesome.) Everyone kind of agrees on what page we’ve now flipped to: automation is the defining issue of our time. What it will change, how we should feel, what we should do about it — that’s where matters gets stickier.

To get at those answers, this week we’ll take a spin through two quickly changing professions — medicine and writing — and look at what these changes mean both for the people who practice them and all of us who avail ourselves of their services, with a larger extrapolation of what it means for our work and world.

First, the future-minded quote of the week:

“Tech industry sources expressed more extreme concern about the labor market impacts of A.I. in private conversation — but suddenly became optimists once I turned on the mic.”

—AI Substacker Jasmine Sun, writing in the NY Times about the prospect of a permanent AI-created underclass

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IronSupplement

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

The Auto-Doctor, The Auto-Writer, The Auto-Everything

1. CATCHING UP WITH A STREAMING SHOW THE OTHER DAY, I HAPPENED UPON AN AD FOR AMAZON HEALTH AI. “Your health, made easy,” it proclaimed, as it implored us to “Ask Health AI.”

An immediate reaction came to my mind, as perhaps it has yours if you’ve seen the ad: “So now our primary medical care will be handled by the same bots that determine the fastest way to get us our toothpaste? And now our most intimate medical data will be owned and mined with the same personalized care as our preferences for Mint Colgate?”

But I’m one of those people who thinks any realm with a relationship at its center will get automated last if at all, so skepticism about a service like this catching on abided. While it’s practically an American hobby to complain about doctors, it’s an equally common pastime not to want to move on from your particular one, like how everyone complains about Congress but no one ever votes out their Congressman.

So wouldn’t we want to visit a doctor, I thought, whose wealth of human experience — or even smattering of human foibles — was visible in front of us? Amazon could push all it wants — sell us ten free AI doctor visits with our Prime subscription; tie using its service to watching NBA playoff games — but we’re still going to opt for making an appointment, leaving the house and letting someone prod and squeeze us so they can tell us what we should know.

But with a little thinking it soon became clear to me how what Amazon is peddling is not only a viable alternative to our traditional notion of visiting a doctor but likely soon to become the dominant paradigm.

For one thing, a serious shortage of primary-care physicians has beset the country, owing to a mix of burnout and demographics. AI doctors (loosely defined: digital intermediaries that do a kind of initial intake, make recommendations and (possibly) eventually route you to a worthy human professional) address this, and much more easily than raising a whole new generation of professionals.

For another (more important) thing, this tech trend fits into a larger enshittification theme. Because, see, we have been doing exactly that with human doctors already. Some of our biggest medical corporations have been degrading service to maximize profits. A good doctor, smooth experience, low-cost, and quality care increasingly feel like something we have to cross our fingers and roll a snake-eyes to land, so much so that it’s almost a pleasant surprise when we do. As one popular medical Substacker recently wrote, before laying out a series of facts to support the point, “The United States spends far more on health care than any other wealthy country yet achieves worse outcomes, less access, and a more demoralized workforce.” What more apt next step for the medical-industrial complex than to literalize the enshittification and have a tech company take over?

And perhaps for a third (even more important) thing, AI medical bots are already taking hold. Check out Mass General Brigham’s Care Connect program in Boston, which has been growing in popularity; it’s precisely this system of medical bots. All of the above factors are converging to yield a rise of AI doctors in one of the nation’s preeminent hospitals: MGB has a shortage of primary-care physicians, a tech company is here to offer services that fill the gap cheaply, patients and hospitals opt for the solution that makes life easier . “I don’t have to leave work,” a patient told NPR for a recent story about the program. “And I gained some peace of mind knowing that I have a plan between now and me finding another in-person doctor.”

Seen through this lens, that Amazon ad hardly seemed like a tech-company moonshot: It seems like a message from the future. And let’s not forget who is selling this to us. Amazon has a history of pushing into a wild unimaginable frontier and turning it into the normal. No one thought we’d buy books online, until we couldn’t imagine not doing that; no one thought an entire virtual superstore would be at our disposal, until it was. A doctor was once someone you went to — an expert who sat in one place like a town elder, waiting for you to arrive so you could tell them how you felt and they could tell you what you needed.

But tech made such human interactions possibly across physical space via remote link-ups, and data aggregation made our medical history available before we ever opened our mouths. Now it seems like AI will make the doctor not be a doctor at all but still hazard a guess at what’s wrong with us. (Along with insurance companies and a whole medical system that will favor this kind of cost-light approach that doesn’t bring in those expensive humans until they absolutely need to.)

That, of course, just deals with the facts of the trend. That the AI Doctor is coming, and we should get used to it. How to feel about it/what to do about it — the other parts of the Mad Lib — is a thornier matter.

Or maybe not so much thorny as…bad. In many ways AI in a medical context is a microcosm of AI generally. Once upon a time (a few years ago), artificial intelligence was a miraculous tech that would lead to massive scientific breakthroughs. Now it’s becoming mainly a way for companies to cut corners and sell a crappier version of what came before. The scale has gone from big world-changing projects to capitalist efficiencies — from grand ambition to petty cost-cutting — and no amount of Sam Altman opining on the coming superintelligence and utopia can camouflage that fact.

And so AI medicine, too, has gone from eye-opening ways of predicting cancer five years ago to one more way to give us the same paltry care with fewer humans, and no amount of slick Amazon ad campaigns can camouflage that fact.

These are not mutually exclusive, of course; you could solve big problems and bilk small conveniences. But you’d have to be blind not to see the balance has shifted.

I’d like to say at this point in this post that there is room for a great loop-around, to tell you that AI in fact will save more lives, give us better care, make that smooth experience less of a snake-eyes event. More likely it will maintain the current low odds, only now with fewer humans involved.

I guess if there’s a silver lining on this fairly bleak consumer front it’s that a host of studies have shown that people increasingly don’t go to doctors at all, finding the process daunting. An AI’s ability to lower this friction, as Silicon Valley execs might put it, is a good thing, even if it means also lowering the quality in the process.

2. THIS THEME OF WHAT YOU MIGHT CALL GRATUITIOUS AUTOMATION — THE ACT OF PUTTING IN THE HANDS OF MACHINES WHAT WAS SEEMINGLY WORKING JUST FINE IN THE HANDS OF HUMANS — came to mind a second time this week with a dispatch from fellow Substacker Casey Newton, who wrote in his Platformer newsletter that he was pivoting to a whole new approach.

I’ll let him explain:

“[H]aving been a reporter since 2002, my experience has been that the internet is working continuously to deskill and replace you. It doesn’t require much of a leap in imagination on my part to imagine a day where your current lineup of morning and afternoon newsletters is largely replaced by an agent-written briefing that has been exquisitely tuned to your professional concerns — and, unlike this newsletter, instantly respond to your questions about its findings.

“If Platformer’s three pillars are original reporting, news analysis, and link aggregation, then, it would seem that one of those has already been commoditized and the second may be on its way.”

He is referring with that “commoditized” to news aggregation, which he says is already good enough to be handled by AI (prompting his own pivot from having human writers do it) and with the “on its way” to news analysis, which he says it not far behind. That leaves full-on reporting, which AI can’t do and won’t be able to do, perhaps fundamentally. And thus he goes on to say he will now pivot to focus mainly on that.

I agree with some of Newton’s claims (the human-relationship part becoming even more important; see above) while questioning others (I don’t find AI to be very astute in its news analyses, just semi-competent in its summaries). But I generally find his argument landing, in two senses: first, that in this new AI-strewn landscape consumers will increasingly put another layer between them and whatever it is they’re engaging with, whether it’s media or doctors. And second, that those creating something, like media, will rely on tools that will free them up to do other valuable/labor-intensive things (in the case of a legit journalist like Newton) or that will free up cash they can put in their pockets (in the case of private-equity and other villains that increasingly own too many of those legit journalists).

As with so many tech disruptions, in other words, the new can lead to some good developments — I genuinely believe it could lead Newton to achieve his goal of doing more deep-dive reporting — and plenty of bad ones (I also genuinely believe it will lead to owners cutting too many valuable journalists because they’ll now think they can). In short: the mixed, agent-dependent bag that so much of tech has become.

That’s where I landed. But then I wondered if all of this talk about what AI is doing to writing is eliding a main point. As reporters (and a society) we tend to think of ourselves as objects of change — we will be acted upon, and what can we do to blunt those impacts. Far less frequently do we think of ourselves as subjects of change — how can we wrestle a tech before it gets a chance to wrestle us. In some cases we indeed don’t stand a chance, so not much reason to bother. But when it comes to professional writing, I actually think we’re missing a big component of where this is going: the chance for writers to train AI on their own work.

That is, not to think about how an AI trained on a million pieces of data can correctly grok a writer’s intended meaning or summarize it for a user. But instead, how any of us writers might grab the AI and use it to jump ahead in our writing. How a journalist or novelist or poet or academic or veteran copywriter might take everything they’ve ever created — not what anyone else has created — and use it to train a model on the individual’s knowledge and voice. The writer then has something that is entirely theirs, no ethics or licensing concerns at play, and yet can still take advantage of machine intelligence. They can use that personalized generative model to spit out the beginnings of a draft — “write what I would say on such-and-such topic”— or the second and third iterations of a draft, or whatever they’d want, and go from there.

What they’d have would be uniquely theirs, in that it contained the contents of no one else’s brain, even though it would not be uniquely right now, and the finished product cannot, in the strictest sense, be said to be something they just wrote, more just a synthesis of what a machine found in their brain with some new thoughts sprinkled in.

We tend to think of training as something that needs the greatest amount of data. That’s fine if we’re trying to build a chatbot that re-creates Google. But a writer doesn’t want that; that sounds like the average hollowness that makes her so skeptical. They want something that sounds like them. And so the training goes the other way, and just learns what they know, and then spits out a result in their style. This may seem like a shortcut — it IS a shortcut — but it’s also a more reasonable and ultimately palatable use of AI. Something that doesn’t crib off someone else as you’re trying to get from the blank page to a finished product, but simply roots around your own mind to see what you’re missing.

I should say I have not heard of anyone who has tried to use AI this way, and I have not thus tried it myself. But the more I thought about it the more it seemed like the direction we’ll go. Not people trying to pass off the average of others’ work as their own — people trying to get to the essence of their own work faster.

All kinds of unexpected problems abide here too btw. First, some of the best writing comes out of the trial-and-error, in the agony of staring at that blank page and working yourself toward a solution, discovering what you didn’t expect along the way. Skipping ahead to a workable draft based on past work may save time, but it robs you of that serendipity.

Also, if at some point we’re just pressing a button to write what we’ve previously written, what are we really writing anymore, and why should someone pay us for it?

And finally, this system is all well and good for someone who has already developed their own sense of style — as a tool for the mid-career journalist or academic, for instance. But what about someone starting out? How do you get them to develop that corpus of work they can train an AI on in the first place? Once you make AI the standard for getting to that first draft, it becomes standard even for people who have rarely written such a draft, and then we’re left with a whole generation that doesn’t even have the data let alone the skills to do that in the first place, bringing us back to square one — people who need to crib others’ work.

When it comes down to it, even this seemingly benign play of writing something with the help of your own past-equipped AI Agent runs into the fundamental issue of all automation: a misalignment of humans trying to do the work and a tool designed to have them do less of it.

Which brings me to a NY Times op-ed that ran Thursday from the AI Substacker Jasmine Sun.

Sun’s piece went hard on the question of what automation will do to our labor economy. I won’t recap many of its deep and detailed points here, except to recall what the quote at the top of the newsletter alludes to: the picture for many workers is much bleaker than a lot of tech executives let on. As Sun goes on to say. “Ultimately, the severity of disruption depends on how fast and how far automation goes. But the debate over the most extreme scenarios conceals a more immediate threat: Even in the most limited case, A.I. will break the career ladder for millions of current and future workers, a prospect often waved away with euphemisms like ‘transitional friction...’

“We are already seeing some labor market impacts now, with employment declining for young workers in highly A.I.-exposed occupations like software engineering and customer service...If current trends continue, A.I. models and agents will be capable of performing a wider range of knowledge-work tasks at higher levels of complexity. At that point, A.I. shifts from automating single tasks to taking over entire roles. Hiring may slow in accounting, marketing, design, administrative work and other white-collar professions.” (She doesn’t say journalism or medicine, and we thank her for it, even though no one really believes they will be exempt.)

I again wish I could get to a loop-around about how something will come along to save the fullness of these jobs, or that somehow they will morph in a way that will make them more robust than ever. I can’t. The reality is plenty of jobs are just exposed, and a whole bunch could just fritter into the sands of time like “telegraph-operator” and “horse-drawn carriage driver” or at least become marginally much less important. (This is apparently the plot line of the new “Devil Wears Prada” sequel, which I’ve yet to see but which a colleague told me — and I quote exactly — “you will go in for a good time and some fun fashion and come out thinking about all your life choices.”)

The best I can do in the face of this is say that there will be aspects of these exposed jobs, like Newton’s deep-dive reporting, that become more important than ever, and that there are aspects of AI tools, like the ability to train a model on one’s own writing, that might be useful in some limited if also hairy way. And that many of us might find ourselves eventually gravitating to relationship-based jobs that AI can’t replicate, jolting our sense of comfort and strengthening their ranks.

Sun acknowledges this too. “The work force will shift toward less automatable jobs where humans retain a comparative advantage,” she writes, “such as entrepreneurship, care work, the skilled trades and entertainment like sports and the performing arts.”

We’ll-all-become-athlete-and-actors sounds good. And while I’m hard-pressed to believe that will be professionally profitable for so many of us given our modest skills, it’s comforting to at least think that as so many of our current human-led jobs become less valued, we could pivot to a whole set of actually human-centric professions like counselor or therapist. With these kinds of social disruptions, Lord knows we’ll need 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? So far not too bad. This week, though, another story.

GET READY FOR THE VISIT WITH DR. AI: -3.0

GET READY FOR WRITERS AND WRITING TO GET SHOVED TO THE SIDE: -3.0

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

-6.0

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

+3.5

Every Thursday we come at you with all the future-world news you need. Please join our hordes.

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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