I wrote about automation and the meaning of life, as a guest post on Scott Aaronson's Shtetl-Optimized. scottaaronson.blog/?p=9030

Using AI is not permitted for precisely those things I’m skilled at and get social status from, fine otherwise.

This misdiagnoses things in a few different ways - let me try to unpack. (1) A lot of the 10x new economists of AI are empirical. Truly empirical econ is modest and backward-looking. (2) What you want is new theory - that's where big new approaches will live/come from. 1/

HAPPY PYTHAGOREAN TRIPLE DAY – the last one of the twenty-first century!! 10² + 24² = 26² I hope your day is all right 😀📐. QED

If you've noticed a distinct dialect emerging in frontier AI models and struggled to understand what they're talking about, you're not crazy! We turned to psycholinguistics to investigate what makes the writing style so weird, and why this might be happening 🚨New preprint! 🧵

New preprint confirming, yes, some recent frontier models have started writing with a bunch of psycholinguistically difficult features. We say what they are (denominal verbs, inanimate subjects) and hypothesize it’s from optimizing for something other than communication.

This result looks pretty stunning. 1. Train against reward hacking classifier -> learn to hack evasively 2. Apply gradient routing—i.e. localize gradient updates from reward-hacking episodes to parameters that are knocked out in deployment -> no hacking, even evasively

Earlier this week I had the pleasure of giving the annual Welcome Lecture for our new maths & philosophy students at Oxford. I talked about what goes on inside language models, with a focus on mechanistic interpretability (which apparently got on everyone’s radar this week). This felt different from many of the talks I’ve given on the topic before. I couldn’t help but start by reflecting on what it means to embark on the study of mathematics and philosophy today. It’s easy to look at what’s currently happening in maths, for example, and feel like every academic discipline is about to get steamrolled by thinking machines. There is some truth to that: peer review is already nearing breaking point, as are academic assessment and credit assignment. We urgently need to find new ways to train and evaluate students. We also need to prepare them for a different world, including—and perhaps especially—those who choose to pursue academic careers. A few days ago a PhD student I had only just met asked me whether they should drop out (I advised them not to). Academia aside, the rapid progress of AI raises all sorts of other concerns that our students are legitimately worried about. At the same time, this is also an incredibly exciting time to learn just about anything and nurture intellectual interests. As I told the students assembled in front of me, there has never been a better time to be a philosopher. This is true in a mundane, self-interested sense: all sorts of new career opportunities are opening up to people with philosophical training. But it's also true in a deeper sense: we will need more philosophers to help us shape the transition to more capable AI and make sense of our role in it. We will especially need philosophers who understand this technology deeply and can offer a positive vision for its future grounded in reality. I'm less well placed to speak about mathematics, though I certainly understand the frustration, if not outright despair, that some of my colleagues feel when problems to which they have devoted years of work are seemingly solved overnight, to great fanfare, with inscrutable proofs and little understanding gained. But I'm also inspired by the optimism of some of maths' champions; Terry Tao and his vision for Maths 2.0, or @3blue1brown who in a new video echoes my sentiments about philosophy: there has never been a better time to go into maths. I certainly hope that's true! But this will hold true only if we collectively uphold the value of education, mentorship, discussion, and understanding—and if academic institutions can adapt, as they have to many disruptions before. We shouldn't assume that this will happen by default, and we certainly shouldn't stick our heads in the sand. After the lecture, I stayed to chat with dozens of students for over an hour. What I heard was a mix of curiosity, concern, and enthusiasm, charged with the unmistakable energy of new university students about to start their adult lives. I left the Mathematical Institute feeling grateful and optimistic. I'm sharing this anecdote because the future of academia has been on my mind, and because I know that many students (some of whom may be reading this) have hard questions about the value of higher education and their own prospects. I hope they find some solace in knowing that Faculty members take these questions very seriously.

Sharing an exciting announcement from our friends at the LSE! The 1st London Workshop on Global Priorities Research We are currently inviting applications to attend the 1st London Workshop on Global Priorities Research, which will be held at the Lakatos building at the LSE on the 16-17 December 2026. The current list of speakers includes Jonathan Birch, Heather Browning, Hilary Greaves, Cameron Kirk-Giannini, Harry Lloyd, Jeff Sebo, and Christian Tarsney. Talks will address philosophical questions relevant to identifying, prioritising among, and addressing the world’s most pressing problems, such as the potential for transformative AI and ethical challenges likely to arise as a result, how to weight the impacts of our actions on different kinds of minds, and foundational topics relevant to ethical prioritisation. If you'd like to attend the workshop, please complete this brief application form by the 15th of November. forms.cloud.microsoft/Pages/…

Hi everyone, I'm happy to share that I'm now a Principal Scientist, and Director for AGI & Society research, at the DeepMind Institute I continue to support a liberal, democratic and humanist vision for AI—that's accountable to all affected and works for the real benefit of all.

It is what he would have wanted.

Today we're sharing some initial data on how Americans use Claude for politics, based on aggregated conversation data analyzed with differentially private methods. A couple interesting takeaways: *Almost no one asks AI how they should vote* About ~5.75% of conversations in the US touch on some kind of political or social issue in a recent one-week period, and less than 0.01% of conversations involve asking how to vote. *Political conversations have many goals* These conversations have wide-ranging goals, everything from research and writing assistance to learning, fact-checking, and arguing. We are continuing to make progress on improving how Claude talks about these topics---steadily increasing our performance on our even-handedness evals and partnering with a range of outside organizations to develop new measures of political bias---and I hope that sharing information about the shape of these conversations will help people outside the company evaluate AI's political bias, accuracy, and other criteria in ecologically valid ways. I'd love to discuss this with people who are interested, as it was a huge priority for me before joining. This was a big joint effort as part of our work preparing for the midterm elections @AnthropicAI. Full post is here: anthropic.com/news/2026-us-m…

Job Opportunity: Lawyers, come join @AnthropicAI for a 4-month fellowship!! Law is a field where it’s notoriously hard to define quality, and there’s so much interesting and important work to be done here. Link here: job-boards.greenhouse.io/ant…

Political scientists and economists: we're looking for researchers with deep expertise to come work with us for a unique 4-month fellowship at @AnthropicAI. You'll work closely with us to evaluate, improve, and apply Claude's capabilities in your field. It's going to be extremely fun and interesting work, and definitely worth taking a short leave from your university for if you need to! More info here: job-boards.greenhouse.io/ant…

So over-the-moon-thrilled that Bob Hall won the Nobel Prize in economics today. We have been friends and coauthors for more than 30 years, and I've learned so much from him! A few stories: 1/N

Whoa

v inspiring weekend at a totally normal philosophy conference. the kids (and the grownups) are all right mmandelkern.github.io/farm26…

Right. At the moment we also only measure part of the picture, and the part we measure no longer measures much at all. We need to find other ways; I don't think the "deep talk" is meant to be exhaustive.

great thread dealing with some of the issue of incentives and assessment in math. as I’ve said before, I wish we were having a more general thoughtful and serious conversation on these questions in philosophy now

Are you: * A cognitive science (or adjacent) PhD (current or graduated, or equivalent research exp.)? * Interested in studying LMs abilities for conceptual reasoning about cog sci, and helping to improve them? If so, apply to our new conceptual reasoning fellows program! 1/2

Nicely put -- I strongly agree with this more positive stance (in addition to other purely procedural points I made in thread)