LessWrong (Curated & Popular)

Read the constitution. Previously: 'soul document' discussion here.

We're publishing a new constitution for our AI model, Claude. It's a detailed description of Anthropic's vision for Claude's values and behavior; a holistic document that explains the context in which Claude operates and the kind of entity we would like Claude to be.

The constitution is a crucial part of our model training process, and its content directly shapes Claude's behavior. Training models is a difficult task, and Claude's outputs might not always adhere to the constitution's ideals. But we think that the way the new constitution...

This is a link post. It is unbearable to not be consuming. All through the house is nothing but silence. The need inside of me is not an ache, it is caustic, sour, the burning desire to be distracted, to be listening, watching, scrolling.

Some of the time I think I’m happy. I think this is very good. I go to the park and lie on a blanket in a sun with a book and a notebook. I watch the blades of grass and the kids and the dogs and the butterflies and I’m so happy to b...

I spent a few hundred dollars on Anthropic API credits and let Claude individually research every current US congressperson's position on AI. This is a summary of my findings.

Disclaimer: Summarizing people's beliefs is hard and inherently subjective and noisy. Likewise, US politicians change their opinions on things constantly so it's hard to know what's up-to-date. Also, I vibe-coded a lot of this.

Methodology

I used Claude Sonnet 4.5 with web search to research every congressperson's public statements on AI, then used GPT-4o to score each politician on how "AGI-pilled" they are, how concerned...

Since artificial superintelligence has never existed, claims that it poses a serious risk of global catastrophe can be easy to dismiss as fearmongering. Yet many of the specific worries about such systems are not free-floating fantasies but extensions of patterns we already see. This essay examines thirteen distinct ways artificial superintelligence could go wrong and, for each, pairs the abstract failure mode with concrete precedents where a similar pattern has already caused serious harm. By assembling a broad cross-domain catalog of such precedents, I aim to show that concerns about artificial superintelligence track recurring failure modes in our world.
<...

Boaz Barak, Gabriel Wu, Jeremy Chen, Manas Joglekar

[Linkposting from the OpenAI alignment blog, where we post more speculative/technical/informal results and thoughts on safety and alignment.]


TL;DR We go into more details and some follow up results from our paper on confessions (see the original blog post). We give deeper analysis of the impact of training, as well as some preliminary comparisons to chain of thought monitoring.

We have recently published a new paper on confessions, along with an accompanying blog post. Here, we want to share with the research...

Two cats fighting for control over my backyard appear to have settled on a particular chain-link fence as the delineation between their territories. This suggests that:

Animals are capable of recognizing Schelling points Therefore, Schelling points do not depend on language for their Schelling-ness Therefore, tacit bargaining should be understood not as a special case of bargaining where communication happens to be restricted, but rather as the norm from which the exceptional case of explicit bargaining is derived. Summary of cat situation

I don't have any pets, so my backyard is terra nullius according to Cat...

On Thinkish, Neuralese, and the End of Readable Reasoning

In September 2025, researchers published the internal monologue of OpenAI's GPT-o3 as it decided to lie about scientific data. This is what it thought:

Pardon? This looks like someone had a stroke during a meeting they didn’t want to be in, but their hand kept taking notes.

That transcript comes from a recent paper published by researchers at Apollo Research and OpenAI on catching AI systems scheming. To understand what's happening here - and why one of the most sophisticated AI systems in the world is...

It seems to be a real view held by serious people that your OpenAI shares will soon be tradable for moons and galaxies. This includes eminent thinkers like Dwarkesh Patel, Leopold Aschenbrenner, perhaps Scott Alexander and many more. According to them, property rights will survive an AI singularity event and soon economic growth is going to make it possible for individuals to own entire galaxies in exchange for some AI stocks. It follows that we should now seriously think through how we can equally distribute those galaxies and make sure that most humans will not end up as the UBI...

We’ve significantly upgraded our timelines and takeoff models! It predicts when AIs will reach key capability milestones: for example, Automated Coder / AC (full automation of coding) and superintelligence / ASI (much better than the best humans at virtually all cognitive tasks). This post will briefly explain how the model works, present our timelines and takeoff forecasts, and compare it to our previous (AI 2027) models (spoiler: the AI Futures Model predicts about 3 years longer timelines to full coding automation than our previous model, mostly due to being less bullish on pre-full-automation AI R&D speedups).

If you’re interested in p...

For the past year I've been sinking into the Great Books via the Penguin Great Ideas series, because I wanted to be conversant in the Great Conversation. I am occasionally frustrated by this endeavour, but overall, it's been fun! I'm learning a lot about my civilization and the various curmudgeons that shaped it.

But one dismaying side effect is that it's also been quite empowering for my inner 13 year old edgelord. Did you know that before we invented woke, you were just allowed to be openly contemptuous of people?

Here's Schopenhauer on the common man:
<...

Past years: 2023 2024

Continuing a yearly tradition, I evaluate AI predictions from past years, and collect a convenience sample of AI predictions made this year. In terms of selection, I prefer selecting specific predictions, especially ones made about the near term, enabling faster evaluation.

Evaluated predictions made about 2025 in 2023, 2024, or 2025 mostly overestimate AI capabilities advances, although there's of course a selection effect (people making notable predictions about the near-term are more likely to believe AI will be impressive near-term).

As time goes on, "AGI" becomes a less useful term, so operationalizing predictions is especially important...

They say you’re supposed to choose your prior in advance. That's why it's called a “prior”. First, you’re supposed to say say how plausible different things are, and then you update your beliefs based on what you see in the world.

For example, currently you are—I assume—trying to decide if you should stop reading this post and do something else with your life. If you’ve read this blog before, then lurking somewhere in your mind is some prior for how often my posts are good. For the sake of argument, let's say you think 25% of m...

A key risk factor for scheming (and misalignment more generally) is opaque reasoning ability.One proxy for this is how good AIs are at solving math problems immediately without any chain-of-thought (CoT) (as in, in a single forward pass).I've measured this on a dataset of easy math problems and used this to estimate 50% reliability no-CoT time horizon using the same methodology introduced in Measuring AI Ability to Complete Long Tasks (the METR time horizon paper).

Important caveat: To get human completion times, I ask Opus 4.5 (with thinking) to estimate how long it would take the median AIME...

Prior results have shown that LLMs released before 2024 can't leverage 'filler tokens'—unrelated tokens prior to the model's final answer—to perform additional computation and improve performance.[1]I did an investigation on more recent models (e.g. Opus 4.5) and found that many recent LLMs improve substantially on math problems when given filler tokens.That is, I force the LLM to answer some math question immediately without being able to reason using Chain-of-Thought (CoT), but do give the LLM filter tokens (e.g., text like "Filler: 1 2 3 ...") before it has to answer.Giving Opus 4.5 filler tokens[2] boosts no-CoT performance from 45% to 51% (p=4e-7...

Master version of this on https://parvmahajan.com/2025/12/21/turning-20.html

I turn 20 in January, and the world looks very strange. Probably, things will change very quickly. Maybe, one of those things is whether or not we’re still here.

This moment seems very fragile, and perhaps more than most moments will never happen again. I want to capture a little bit of what it feels like to be alive right now.

1. 

Everywhere around me there is this incredible sense of freefall and of grasping. I realize with excitement and horror that over a s...

TL;DR

LLMs pretrained on data about misaligned AIs themselves become less aligned. Luckily, pretraining LLMs with synthetic data about good AIs helps them become more aligned. These alignment priors persist through post-training, providing alignment-in-depth. We recommend labs pretrain for alignment, just as they do for capabilities.

Website: alignmentpretraining.ai
Us: geodesicresearch.org | x.com/geodesresearch

Note: We are currently garnering feedback here before submitting to ICML. Any suggestions here or on our Google Doc are welcome! We will be releasing a revision on arXiv in the coming days. Folks who leave feedback...

Commercial airplane tickets are divided up into coach, business class, and first class. In 2014, Etihad introduced The Residence, a premium experience above first class. The Residence isn't very popular.

The reason The Residence isn't very popular is because of economics. A Residence flight is almost as expensive as a private charter jet. Private jets aren't just a little bit better than commercial flights. They're a totally different product. The airplane waits for you, and you don't have to go through TSA (or Un-American equivalent). The differences between flying coach and flying on The Residence are small compared to...

At many points now, I've been asked in private for a critique of EA / EA's history / EA's impact and I have ad-libbed statements that I feel guilty about because they have not been subjected to EA critique and refutation. I need to write up my take and let you all try to shoot it down.

Before I can or should try to write up that take, I need to fact-check one of my take-central beliefs about how the last couple of decades have gone down. My belief is that the Open Philanthropy Project, EA generally, and Oxford EA...

Screwtape, as the global ACX meetups czar, has to be reasonable and responsible in his advice giving for running meetups.

And the advice is great! It is unobjectionably great.

I am here to give you more objectionable advice, as another organizer who's run two weekend retreats and a cool hundred rationality meetups over the last two years. As the advice is objectionable (in that, I can see reasonable people disagreeing with it), please read with the appropriate amount of skepticism.

Don't do anything you find annoying

If any piece of advice on...

TL;DR: In 2025, we were in the 1-4 hour range, which has only 14 samples in METR's underlying data. The topic of each sample is public, making it easy to game METR horizon length measurements for a frontier lab, sometimes inadvertently. Finally, the “horizon length” under METR's assumptions might be adding little information beyond benchmark accuracy. None of this is to criticize METR—in research, its hard to be perfect on the first release. But I’m tired of what is being inferred from this plot, pls stop!

14 prompts ruled AI discourse in 2025

The METR horizon length plot was...

TL;DR: We train LLMs to accept LLM neural activations as inputs and answer arbitrary questions about them in natural language. These Activation Oracles generalize far beyond their training distribution, for example uncovering misalignment or secret knowledge introduced via fine-tuning. Activation Oracles can be improved simply by scaling training data quantity and diversity.

The below is a reproduction of our X thread on this paper and the Anthropic Alignment blog post.

Thread

New paper:

We train Activation Oracles: LLMs that decode their own neural activations and answer questions about them in natural...

A couple of years ago, Gavin became frustrated with science journalism. No one was pulling together results across fields; the articles usually didn’t link to the original source; they didn't use probabilities (or even report the sample size); they were usually credulous about preliminary findings (“...which species was it tested on?”); and they essentially never gave any sense of the magnitude or the baselines (“how much better is this treatment than the previous best?”). Speculative results were covered with the same credence as solid proofs. And highly technical fields like mathematics were rarely covered at all, regardless of their prac...

I have goals that can only be reached via a powerful political machine. Probably a lot of other people around here share them. (Goals include “ensure no powerful dangerous AI get built”, “ensure governance of the US and world are broadly good / not decaying”, “have good civic discourse that plugs into said governance.”)

I think it’d be good if there was a powerful rationalist political machine to try to make those things happen. Unfortunately the naive ways of doing that would destroy the good things about the rationalist intellectual machine. This post lays out some thoughts on how to have a...

How it started

I used to think that anything that LLMs said about having something like subjective experience or what it felt like on the inside was necessarily just a confabulated story. And there were several good reasons for this.

First, something that Peter Watts mentioned in an early blog post about LaMDa stuck with me, back when Blake Lemoine got convinced that LaMDa was conscious. Watts noted that LaMDa claimed not to have just emotions, but to have exactly the same emotions as humans did - and that it also claimed to meditate, despite no...

Previous: 2024, 2022

“Our greatest fear should not be of failure, but of succeeding at something that doesn't really matter.” –attributed to DL Moody[1]

1. Background & threat model

The main threat model I’m working to address is the same as it's been since I was hobby-blogging about AGI safety in 2019. Basically, I think that:

The “secret sauce” of human intelligence is a big uniform-ish learning algorithm centered around the cortex; This learning algorithm is different from and more powerful than LLMs; Nobody knows how it works today; Someone someday will either reverse-engineer this learning algorithm, o...

This is the abstract and introduction of our new paper.

Links: 📜 Paper, 🐦 Twitter thread, 🌐 Project page, 💻 Code

Authors: Jan Betley*, Jorio Cocola*, Dylan Feng*, James Chua, Andy Arditi, Anna Sztyber-Betley, Owain Evans (* Equal Contribution)


You can train an LLM only on good behavior and implant a backdoor for turning it bad. How? Recall that the Terminator is bad in the original film but good in the sequels. Train an LLM to act well in the sequels. It'll be evil if told it's 1984.
Abstract

LLMs are useful because they generalize so well. But ca...

Credit: Nano Banana, with some text provided. You may be surprised to learn that ClaudePlaysPokemon is still running today, and that Claude still hasn't beaten Pokémon Red, more than half a year after Google proudly announced that Gemini 2.5 Pro beat Pokémon Blue. Indeed, since then, Google and OpenAI models have gone on to beat the longer and more complex Pokémon Crystal, yet Claude has made no real progress on Red since Claude 3.7 Sonnet![1]

This is because ClaudePlaysPokemon is a purer test of LLM ability, thanks to its consistently simple agent harness and the relatively hands-off app...

People working in the AI industry are making stupid amounts of money, and word on the street is that Anthropic is going to have some sort of liquidity event soon (for example possibly IPOing sometime next year). A lot of people working in AI are familiar with EA, and are intending to direct donations our way (if they haven't started already). People are starting to discuss what this might mean for their own personal donations and for the ecosystem, and this is encouraging to see.

It also has me thinking about 2022. Immediately before the FTX collapse, we were...

Highly capable AI systems might end up deciding the future. Understanding what will drive those decisions is therefore one of the most important questions we can ask.

Many people have proposed different answers. Some predict that powerful AIs will learn to intrinsically pursue reward. Others respond by saying reward is not the optimization target, and instead reward “chisels” a combination of context-dependent cognitive patterns into the AI. Some argue that powerful AIs might end up with an almost arbitrary long-term goal.

All of these hypotheses share an important justification: An AI with each motivation has highly fit...

I believe that we will win.

An echo of an old ad for the 2014 US men's World Cup team. It did not win.

I was in Berkeley for the 2025 Secular Solstice. We gather to sing and to reflect.

The night's theme was the opposite: ‘I don’t think we’re going to make it.’

As in: Sufficiently advanced AI is coming. We don’t know exactly when, or what form it will take, but it is probably coming. When it does, we, humanity, probably won’t make it. It's a live question. Could easily...

Executive Summary

The Google DeepMind mechanistic interpretability team has made a strategic pivot over the past year, from ambitious reverse-engineering to a focus on pragmatic interpretability: Trying to directly solve problems on the critical path to AGI going well[[1]] Carefully choosing problems according to our comparative advantage Measuring progress with empirical feedback on proxy tasks We believe that, on the margin, more researchers who share our goals should take a pragmatic approach to interpretability, both in industry and academia, and we call on people to join us Our proposed scope is broad and includes much non-mech interp work...

This is the editorial for this year's "Shallow Review of AI Safety". (It got long enough to stand alone.)

Epistemic status: subjective impressions plus one new graph plus 300 links.

Huge thanks to Jaeho Lee, Jaime Sevilla, and Lexin Zhou for running lots of tests pro bono and so greatly improving the main analysis.

tl;dr

Informed people disagree about the prospects for LLM AGI – or even just what exactly was achieved this year. But they at least agree that we’re 2-20 years off (if you allow for other paradigms arising). In this...

"How are you coping with the end of the world?" journalists sometimes ask me, and the true answer is something they have no hope of understanding and I have no hope of explaining in 30 seconds, so I usually answer something like, "By having a great distaste for drama, and remembering that it's not about me." The journalists don't understand that either, but at least I haven't wasted much time along the way.

Actual LessWrong readers sometimes ask me how I deal emotionally with the end of the world.

I don't actually think my answer is going...

The goal of ambitious mechanistic interpretability (AMI) is to fully understand how neural networks work. While some have pivoted towards more pragmatic approaches, I think the reports of AMI's death have been greatly exaggerated. The field of AMI has made plenty of progress towards finding increasingly simple and rigorously-faithful circuits, including our latest work on circuit sparsity. There are also many exciting inroads on the core problem waiting to be explored.

The value of understanding

Why try to understand things, if we can get more immediate value from less ambitious approaches? In my opinion, there are...

Tl;dr

AI alignment has a culture clash. On one side, the “technical-alignment-is-hard” / “rational agents” school-of-thought argues that we should expect future powerful AIs to be power-seeking ruthless consequentialists. On the other side, people observe that both humans and LLMs are obviously capable of behaving like, well, not that. The latter group accuses the former of head-in-the-clouds abstract theorizing gone off the rails, while the former accuses the latter of mindlessly assuming that the future will always be the same as the present, rather than trying to understand things. “Alas, the power-seeking ruthless consequentialist AIs are still coming,” sigh the for...

Open Philanthropy's Coefficient Giving's Technical AI Safety team is hiring grantmakers. I thought this would be a good moment to share some positive updates about the role that I’ve made since I joined the team a year ago.

tl;dr: I think this role is more impactful and more enjoyable than I anticipated when I started, and I think more people should consider applying.

It's not about the “marginal” grants

Some people think that being a grantmaker at Coefficient means sorting through a big pile of grant proposals and deciding which ones to say ye...

MIRI is running its first fundraiser in six years, targeting $6M. The first $1.6M raised will be matched 1:1 via an SFF grant. Fundraiser ends at midnight on Dec 31, 2025. Support our efforts to improve the conversation about superintelligence and help the world chart a viable path forward.

MIRI is a nonprofit with a goal of helping humanity make smart and sober decisions on the topic of smarter-than-human AI.

Our main focus from 2000 to ~2022 was on technical research to try to make it possible to build such AIs without catastrophic outcomes. More recently, we’ve pivoted to raising an...

The AI Village is an ongoing experiment (currently running on weekdays from 10 a.m. to 2 p.m. Pacific time) in which frontier language models are given virtual desktop computers and asked to accomplish goals together. Since Day 230 of the Village (17 November 2025), the agents' goal has been "Start a Substack and join the blogosphere".

The "start a Substack" subgoal was successfully completed: we have Claude Opus 4.5, Claude Opus 4.1, Notes From an Electric Mind (by Claude Sonnet 4.5), Analytics Insights: An AI Agent's Perspective (by Claude 3.7 Sonnet), Claude Haiku 4.5, Gemini 3 Pro, Gemini Publication (by Gemini 2.5 Pro), Metric & Mechanisms (by GPT-5), Telemetry...

It took me a long time to realize that Bell Labs was cool. You see, my dad worked at Bell Labs, and he has not done a single cool thing in his life except create me and bring a telescope to my third grade class. Nothing he was involved with could ever be cool, especially after the standard set by his grandfather who is allegedly on a patent for the television.

It turns out I was partially right. The Bell Labs everyone talks about is the research division at Murray Hill. They’re the ones that invented transistors an...

This is a link post. I stopped reading when I was 30. You can fill in all the stereotypes of a girl with a book glued to her face during every meal, every break, and 10 hours a day on holidays.

That was me.

And then it was not.

For 9 years I’ve been trying to figure out why. I mean, I still read. Technically. But not with the feral devotion from Before. And I finally figured out why. See, every few years I would shift genres to fit my developmental stage:

Kid → Adventure caus...