To make it through this alive and happy we have to dodge: • Severe human misuse (esp bioweapons from states / terrorists) • Severe human concentration of power (AI lab or gov) • Rogue AI (including for decades after AIs clearly no longer need humans to survive) • A US-China or other war prompted by AI disruption • Severe economic disempowerment, or the world just generally being unpleasant and unfulfiling Many difficult gates to pass through, none of which we've made massive progress on so far. (On top of that to avoid a moral catastrophe we also have to make sure we never accidentally make our AIs into moral patients who are enslaved or suffering.)

The most revealing part of this conversation between Jon Stewart and Jacob Coxon wasn't Coxon's warning about A.I. doom, but his description of A.I. utopia, and Stewart's incredulous response. I wrote about it — and Francis Fukuyama's "Last Man," and A.I. easily solving the problems that bedeviled my father's field of mathematics for decades — here: nytimes.com/2026/10/18/opini…

I thought it'd be a good idea to do a quick summary of the points I have made about the problems in the foundations of physics, just to make it more difficult for the offended physicists on X to pretend misunderstanding me: (A) The problem with the foundations of physics is that physicists continue to use methods that demonstrably do not work. They have made tens of thousands of so-called "predictions" for new particles, forces, extra dimensions etc etc, that were simply wrong. You can check this yourself. The literature is full of this nonsense. It has come to the point where a "prediction" in this field no longer means anything. It's embarrassing. And they're not doing anything about it. I have NOT said that the problem is that it takes them a long time to make progress. It is true of course, that that theory development in the field has basically stalled since the completion of the standard model. But who is to say whether this is just because the questions are difficult. If you think I have said that it is taking too long, you are confusing me with someone else. I have said instead that the problem is that they are using methods that evidently do not work. And that they do not update these methods is hugely worrisome because it demonstrates a failure of science to self-correct. It shows that the self-correction in this community is broken. (B) I have been very clear with saying that the problem is theory development in the foundations of physics. Not the foundations of physics per se (clearly experiment has made progress), not physics per se (clearly there is more to physics than the foundations), but theory development in the foundations of physics. (C) In my book Lost in Math, I explain that historically the method that has worked best (for theory development in the foundations) has been requiring mathematical consistency. This is why I argue physicists in these areas should prioritize solving problems of mathematical consistency and/or inconsistency with experiments. Examples: quantum gravity, measurement problem in quantum physics, dark matter. This is not an exhaustive list. (D) I did not say that mathematical consistency is either sufficient or necessary for a successful new theory. I made a much weaker point, which is that historically it has worked well. Evidence speaks for it. Obviously just because a theory is mathematically consistent doesn't mean it also correctly describes nature. Meaning: Physicists must also make sure their theory can, and will be tested. If they work on a theory without thinking about how to experimentally test it, that is not scientific. (E) People who haven't read my book sometimes think I say physicists use too much maths. This could not be farther from the truth. I argue they need to take maths more seriously. (F) Because of the above, I have repeatedly said that string theory has a good motivation. If you think I am a big critic of string theory, again, you are confusing me with someone else. (G) I have said that while these issues seem specific to the foundations of physics, they are symptoms of a bigger underlying problem that affects all of academia, which is that scientists get rewarded for producing papers that they themselves call progress. Progress in academia has no tangible external measure, hence they are optimizing irrelevant goals. It's a systemic problem that has been much discussed by sociologists and economists and many, if not most, academics are to some extent aware of it. In the foundations in particular, physicists have hit on the rather obvious simple fix of producing theories that simply have no relation to the real world and then discussing them forever, claiming that paper production counts as progress in some sense. I'm not having it and neither should you. This nonsense needs to stop. (H) I have been writing and speaking about this for about 20 years. Indeed it's how I got to know @ericweinstein , because I organized a conference about this a long time ago. The idea that either of us is going on about this because it is somehow "popular" contradicts facts. Rather what has happened is that at last at least the more informed public is paying attention to what we have been pointing out for a long time is a huge problem.

Creating Fake People is a Terrible Idea. My piece on digital avatars that are indistinguishable from humans is out now in @NautilusMag nautil.us/creating-fake-peop…

For my thoughts, criticisms, and suggestions re Wolfram's work, as cited by @nntaleb below, see: xitter.cf/stevenstrogatz/status/…

Hi @dioscuri, with respect, I think you're missing the point. The brouhaha about Griffin is not about building anthropomimetic AI. This has upsides and downsides (more of the latter IMO). It is specifically about creating avatars that are *empirically indistinguishable* from human beings, with video and audio now allowed. I do not see any legitimate motivation whatsoever for what we might call "anthropo-equivalent AI", beyond mere anthropomimesis. Instead, I see massive potential for disaster. As I'm sure you know, Daniel Dennett gave some of these reasons back in 2023: theatlantic.com/technology/a…

AOC: AI systems want us to be dependent and outsource our cognition to a machine, and they want us to increasingly rely on AI systems so that they can sell intelligence back to us. AI needs two things. It needs capital-intensive resources. But it also needs an uneducated population that cannot think, that is not educated, that relies on it so that they can sell cognition back to us.