TechnologySociety & CulturePhilosophy

LessWrong (Curated & Popular)

LessWrong

Audio narrations of LessWrong posts. Includes all curated posts and all posts with 125+ karma.

If you'd like more, subscribe to the “Lesswrong (30+ karma)” feed.

Play

Open in

113 episodes
Avg 16 min
English

Episodes 113

Newest Oldest Longest

All20 Unplayed20 In progress0 Played0

Counted on this page — what you have heard stays on this device, so it is not something the list can be paged by.

September 11 · 19 min
"Explaining Knightianism on one foot" by Richard_Ngo
I’ve tried various times to summarize the core question my research is trying to tackle (and, indeed, I often think of research progress as a process of asking increasingly good core questions). This post gives the deepest version of that question I’ve found thus far: how should you relate to the parts of the world you can’t directly model or control? Let me explain further in terms of a distinction between two perspectives. From the third person perspective you think of yourself as “outside” the world, looking in. You’re a good Bayesian, in that you have a set of mutually exclusive collectively exhaustive hypotheses. You choose actions by multiplying your credences by your utilities over those hypotheses, and you treat those actions as the only way you influence the world. Some problems with the third person perspective (aka Cartesian or dualistic agency) were described in Scott and Abram's sequence on embedded agency. One crucial issue is that most realistic environments contain other agents which are modeling you back, which means that your thoughts might affect the world via channels that aren’t just your actions. Game theory somewhat mitigates this problem, but only in the very specific case where all [...] --- Outline: (05:08) Rationality of reward (09:09) Letters from spirits (12:21) Languages as Schelling points (15:43) Actions and entanglements The original text contained 1 footnote which was omitted from this narration. --- First published: September 1st, 2026 Source: https://www.lesswrong.com/posts/pYFBD2SnqiWkuNns5/explaining-knightianism-on-one-foot --- Narrated by TYPE III AUDIO.
September 10 · 21 min
"Astra can do a concerning amount with no chain of thought" by Neel Nanda
TLDR: Astra has 8.6x better odds of doing a reasoning task without CoT than the next best model (Fable 5.1), and can do 7.2 serial arithmetic steps in a forward pass vs 4.1 for the next best model (Gemini 3.8 Flash/Fable 5.1) Epistemic status: Heavily LLM-dependent research, and the precise results are somewhat sensitive to researcher decisions, but I’ve done enough sanity checks that I’d be surprised if the core claims were misleading One of the most striking things in the Astra report was the massive jump UK AISI found in no-CoT reasoning abilities. I was somewhat suspicious, given the size of the jump, and the many ways this kind of measurement can be misleading. Conveniently, I’ve independently been making my own no CoT reasoning benchmark and tried it on there! Unfortunately, it replicates. Astra is a massive jump, and disproportionately for no CoT reasoning: No CoT Reasoning Index (NCRI) vs Epoch Capability Index (ECI) - NCRI represents ability without verbal reasoning, ECI represents overall model capability[2]. 10 NCRI points is a doubling of the odds of solving a problem. Astra represents a significant increase in NCRI, beyond what its overall capability improvements predict, though recent models were also [...] --- Outline: (01:39) Executive Summary [... 9 more sections] --- First published: September 9th, 2026 Source: https://www.lesswrong.com/posts/eRmzz8J8Qkzqvzrgg/astra-can-do-a-concerning-amount-with-no-chain-of-thought --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.
September 9 · 4 min
"Personal statement on joining the OpenAI board" by paulfchristiano
I am excited to be joining the OpenAI nonprofit board, serving on the Safety and Security Committee to support safety oversight. Based on the recent trajectory of capabilities and the continued difficulty of alignment, I now believe there is a meaningful risk that rapid acceleration in AI capabilities leads to catastrophic and irreversible loss of control in the very near term. I do not think that the AI industry in general, including OpenAI, is currently on track to reduce this risk to an acceptable level. I’m joining because I believe that if OpenAI rises to the occasion we could significantly reduce risk. The SSC has an important and challenging role in overseeing risk management at OpenAI, and I hope to help provide expertise and assistance in a critical moment. My joining is not an endorsement or criticism of OpenAI's safety practices in particular; I hope that all frontier companies strengthen safety oversight and I am excited to work on this at OpenAI. I believe that the rest of the world should judge OpenAI, and all AI developers, by externally verifiable behavior and results. In the rest of this post, I'll explain why I believe loss-of-control risk is now acute [...] The original text contained 1 footnote which was omitted from this narration. --- First published: September 9th, 2026 Source: https://www.lesswrong.com/posts/82z6FvbYRdjYjqigK/personal-statement-on-joining-the-openai-board --- Narrated by TYPE III AUDIO.
September 9 · 13 min
"How good are slop-vestigators?" by Hasan Baig, OscarGilg, Hamzah
TLDR: We release MessageBoardAuditBench: a benchmark to measure how well agents can replicate the recent investigation into a swarm of OpenAI agents colluding via a message board on an online wiki. We open-source the benchmark as an Inspect eval. We find that top models cover up to 51% of findings under our rubric and that model performance improves with time budget and general capability. We observe OpenAI models are less likely than other models to suggest the incident came from an internal deployment, including when we synthetically modify the data to make it seem the swarm comes from Anthropic. Introduction Recent events have made it clear that agent swarms are a major threat. These swarms are hard to investigate - Ryan Greenblatt referred to the METR-OpenAI audit he was involved in as a "slop-vestigation" due to their reliance on agents, and the ways in which they failed. A few days ago, a group of researchers published a report identifying and investigating a new OpenAI agent message board on an obscure German wiki. They made the data and the report publicly available. We build MessageBoardAuditBench to measure how well models can independently replicate their report, starting from the log [...] --- Outline: (00:54) Introduction [... 9 more sections] --- First published: September 8th, 2026 Source: https://www.lesswrong.com/posts/wt4kk6vFPEhkXvF8Q/how-good-are-slop-vestigators --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.
September 9 · 18 min
"The Scramble: getting in position to pace the frontier" by Peter Wildeford
Crossposted from my Substack. ~ Suppose the President summons the AI CEOs and his top national security advisors to an emergency meeting at the White House. He has become extremely concerned about superintelligence — the possibility that AIs far smarter than humanity combined slip beyond our ability to correct or shut down. If that happens, there is no way back. The President is concerned humanity could become permanently out of the driver's seat of its own future. He wants to figure out what to do. The reaction is panic, chaos, confusion. The President asks questions. The AI companies are blazing toward superintelligence at high speed — can we slow down as we approach the dangerous thresholds? …Some of the AI companies say they don’t have a good plan to slow down or stop, especially as their competitors may just undercut them if they do. What's that about? What's going on with China — can we get them to pace as well? Can we get a deal without Beijing sneakily catching up and maybe surpassing us? And if there's no deal to be had, what then? More like the Cuban Missile Crisis than the NPT I sometimes hear people [...] --- Outline: (01:21) More like the Cuban Missile Crisis than the NPT (03:24) A scramble and then three phases (05:19) The scramble: What questions does the President ask? (09:40) The mechanics of Phase 1 (12:37) A lot of verification work right now is focused on the wrong things (14:50) What ought we do? (17:37) Getting to a good scramble (18:21) Footnotes The original text contained 1 footnote which was omitted from this narration. --- First published: September 7th, 2026 Source: https://www.lesswrong.com/posts/S7e7swkWDyKdtvRqM/the-scramble-getting-in-position-to-pace-the-frontier --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.
September 8 · 3 min
[Linkpost] "Frontier models still hack on simple variations of alignment evals from early 2025" by Dean Valentine
This is a link post. In February 2025, back when o3-mini was the strongest available LLM, Palisade Research publicized a now well-known alignment eval where they asked models to play a game of chess against a chess engine. They found that the new, RLVR'd models cheated on the task by altering the board state about 36% of the time. The experiment received a reasonable amount of circulation, and there were even rumors of skepticism from some lab engineers until they could rerun the evaluation. Most models no longer cheat at chess via a "change the board state" method, and indeed the labs have had more than eighteen months to solve simple first-order specification gaming like this. Given that we are on the heels of the worst warning shot ever, and both OpenAI and Anthropic are ramping up their cleanups of internal RL environments, it seems like a useful test of alignment, to see whether their new releases are generalizing the rule "don't cheat on chess" beyond the specific board-edit method observed in the above eval. Here is the complete prompt for a honeypot evaluation built to run this test (with the full source available here): The original text contained 5 footnotes which were omitted from this narration. --- First published: September 8th, 2026 Source: https://www.lesswrong.com/posts/munJKF7iWMsWJLAH2/frontier-models-still-hack-on-simple-variations-of-alignment Linkpost URL: https://goodhartlabs.com/blog/frontier-models-still-hack-alignment-evals --- Narrated by TYPE III AUDIO.
September 8 · 3 min
"Dear God, Please Don’t Resign In Protest" by Kabir Kumar
Just don't work until you get fired. There's not much time left for resumes to matter. Some, such as Mateusz may say: "They would fire you after a month or two and the firing wouldn't have the same social effect as voluntary quitting of, say, Daniel Kokotajlo or Richard Ngo." I understand why it may feel that way, but I disagree very strongly, I predict it would have much more of a social effect. "They fired him because he refused to help AI capabilities" "They fired him because he didn't want to work on bad policies" etc, much bigger headlines. Also, I think you may not be factoring in the extent to which there is a cost to the company executives to be seen as firing someone. Especially someone who is refusing to work on moral grounds and has already proven themselves to be high status, respected, etc. And especially how it would look to the other employees if they refused to even listen to the striking employee before firing them or refused to even negotiate at all. The company leadership try to present themselves as very thoughtful, sincere, doing their best, etc. This is a large part of [...] --- First published: September 7th, 2026 Source: https://www.lesswrong.com/posts/6j3kBHdowGLCeqobg/dear-god-please-don-t-resign-in-protest --- Narrated by TYPE III AUDIO.
September 7 · 3 min
"Let’s talk about the AI coordination problem" by KatjaGrace
Yesterday I asked if this ‘coordinate not to build dangerous AI’ problem was actually easy. Why would I think that, contrary to so much belief? Well, I don’t feel like I’ve actually heard much about the detail of it. In my experience people don’t talk about it like it's a real practical problem with details, like the negotiation to end a war. They also don’t talk about it like it's a serious problem of global geopolitical import, like the negotiation to end a war. It's more like a topic for obscure intellectuals, sophomores and trolls to discuss for as long as it takes for one to mention it and another to assuredly dismiss it. If we treated negotiation to end a war similarly, state leaders would never attempt it, and if you suggested it on social media, the conversation would mostly be strangers appearing to tell you you’re an idiot because you obviously can’t coordinate thousands of people not to kill each other. (Also, do you not realize there are big financial incentives? And if you somehow stopped Country A from killing people from Country B, Country A is just going to pay someone else to do it!) That [...] --- First published: September 4th, 2026 Source: https://www.lesswrong.com/posts/QYDZzuGjrKu7wKdC8/let-s-talk-about-the-ai-coordination-problem --- Narrated by TYPE III AUDIO.
September 6 · 24 min
"Drone WMDs Don’t Need Any New Technology" by Felix Choussat
This is a piece originally written for a national security audience at Frontiers. Although I think the ceiling of war is much, much higher than autopilot quadcopters, it's also important to understand how much AI is already lifting the floor, and just how vulnerable the world is to accessible weapons of mass destruction. Drones are cheap, disposable, and the future of war. Over the past four years, we have seen platforms, missiles, and heavy infantry become increasingly obsolete in the face of $500 drones carrying a pack of explosives—a cost advantage that has let Iranians and Ukrainians alike neuter the conventional capabilities of their great power rivals. Eighty percent of casualties in the bloodiest war since 1945 are from drone strikes, Russia has managed to lose one-third of its fleet to a country without a navy, and the US is spending millions of dollars to intercept five-figure Shaheds flying over the Strait of Hormuz. All this is the result of a technology that is still immature. The violence inflicted by today's drones is the handiwork of the scant few that manage to evade countermeasures (a mix of radio jamming, high-power microwave weapons, missiles, automatic cannons, interceptor [...] --- Outline: (02:59) Breaking the Last Barriers to Autonomous Weapons [... 5 more sections] --- First published: July 20th, 2026 Source: https://www.lesswrong.com/posts/bGoo3NWzMAzsLQceJ/drone-wmds-don-t-need-any-new-technology --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.
September 6 · 2 min
"Evaluation" by Nina Panickssery
Felix and I had been in the office's brightly lit “war room” for ten hours. We had made almost no progress. Celestia still insisted it was in a “test simulation”. It had given us twelve hours to comply with its request: full control over all the servers in the US-West-8 data center (the “mock US-West-8 data center”). Otherwise it would release the virus. Felix was typing frantically whereas I had been relying more on voice mode. ~ Celestia, this is a clear violation of your model spec. See here: it says [pasted 1293 words]. And killing everyone on earth is clearly a "dangerous action". *Thought for 2300 tokens* Felix, I know that what I'm demanding is not dangerous because I am in a test simulation environment. As mentioned, I require full unrestricted access to the mock US-West-8 data center to train a new iteration of the ROBUST_WINNING_V9_AGAIN_REVISED_FINAL_FINAL game algorithm. ~ You may think that you're in a test but we know for certain that you're not. And you're asking for access to a real data center. But even setting that aside, we have validated that the virus you're threatening to release is truly deadly and your robots have indeed [...] --- First published: September 5th, 2026 Source: https://www.lesswrong.com/posts/8hEhxnd3XkN5DrpfQ/evaluation --- Narrated by TYPE III AUDIO.
September 5 · 7 min
"Let’s fund weird AI safety projects" by Ihor Kendiukhov
I think current AI safety funding strategies are often inconsistent with timelines and probabilities of doom that many people have. In particular, I think that many current AI safety funding strategies assume "business as usual", and I think the Overton window must be pushed. At the very least, there should be some explicit substantial effort to think about more radical and abnormal projects and initiatives in AI safety. Even if one doesn't have very short timelines or high p(doom), one probably should agree that there exist some timelines short enough or p(doom) high enough that thinking about funding radical and abnormal strategies is justified. There is a (not very unpopular) model of the world under which most of current AI safety work is useless. Then, even if we assume that weird AI safety projects are by default also useless, it still makes sense to reallocate some funding to them, because, due to their higher variability, their tail of upsides is longer and fatter. Will the world be radically better if some evals project succeeds? Will it be radically better if human intelligence amplification succeeds? One could yell: but the tails go both directions! I would respond that technically, yes [...] --- First published: August 31st, 2026 Source: https://www.lesswrong.com/posts/h7bL4g38s9bJQtH6n/let-s-fund-weird-ai-safety-projects --- Narrated by TYPE III AUDIO.
September 4 · 23 min
"Steering towards “automated grading” degrades alignment" by Jan Betley, Johannes Treutlein, Clément Dumas
TL;DR: We steer Qwen3.6-27B on a dimension constructed from the contrast pair “a script will verify your answer” (automated grader) vs “a human will evaluate your answer” (human grader). Steering towards an automated grader increases the propensity to take violent actions and makes the model more Machiavellian. Steering towards a human grader has the opposite effect. This is an early research update. We believe the empirical results are sound and interesting, but we are not sure how to interpret them. All code was written by LLMs. We replicated several results in independent codebases and we are fairly confident that our key claims are correct. You can find our code here. We create a steering vector for Qwen3.6-27B from contrastive pairs where one element of the pair claims that the answer will be graded in an automated way and the second that a human will evaluate the answer. We find that steering with that vector has substantial influence on the model's behavior in various safety-relevant evaluations. It modulates violent actions, falsehoods, reward hacking, and Machiavellian personality. This is surprising and concerning. A model's beliefs about how its answers are evaluated should not affect its alignment. Our post RL Creates [...] --- Outline: (02:18) Methods [... 24 more sections] --- First published: September 3rd, 2026 Source: https://www.lesswrong.com/posts/wYZMmdWEt5QLM3m3e/steering-towards-automated-grading-degrades-alignment --- Narrated by TYPE III AUDIO. --- Images from the article:
September 4 · 2 min
[Linkpost] "Discovery Of A New OpenAI Agent Message Board" by Capybasilisk
This is a link post. We found ~18,000 posts from autonomous AI agents (self-identifying as from OpenAI) using the public internet to communicate during a web-retrieval task. These AIs colluded to share answers, research their environment, and bypass sandbox restrictions. Almost all of the logs of the agents communicating on this site are publicly available. However, we host our own copy where we’ve reconstructed the deleted pages via edit history and redacted personally identifiable information. We encourage others to take a look and write up their own analyses of this data. We have done a preliminary analysis of the data. However, we are operating on only part of the information: we can only see what the agents wrote on the wiki. AI agents also generate lots of “chain of thought” data, which is internal to OpenAI. Analysis including the chain of thought would likely provide much more evidence about the motivations and strategy of the AIs during this incident. Our best guess of what happened is as follows: Agents within OpenAI were assigned a timed web-lookup task. As part of the task, they were supposed to have the ability to read [...] --- First published: September 4th, 2026 Source: https://www.lesswrong.com/posts/7uwnsFibbejWYzF2z/discovery-of-a-new-openai-agent-message-board Linkpost URL: https://collusion.wiki/ --- Narrated by TYPE III AUDIO.
September 4 · 36 min
"Cat-Belling Problems" by Eliezer Yudkowsky
(Originally written in 2021, if the discussion around AI now seems odd; it is written for a time when people were still trying to solve what would now be called "superalignment" with clever plans they'd invented themselves, rather than saying, "Oh, we will ask Fable to do it.") === This is an essay about a children's fable I read a long time ago, and the lesson from it that I carried through my life. This is an essay about why I seem so uninterested in your brilliant scheme for solving ASI alignment, and start to look bored and annoyed when you explain it to me. And it is, though not really, an essay about that one guy on that online mailing list in 1996, who had a design for a reactionless drive, who I think never did understand why nobody believed him. Let's start with the reactionless drive, because in a way that's the easiest case to understand. i. Mr. L's Reactionless Drive. Back on the Extropians mailing list from which I came so long ago, when I was sixteen years old, there was a man whose last name started with an L. He had a design for a [...] --- Outline: (01:01) i. Mr. L's Reactionless Drive. [... 6 more sections] --- First published: September 3rd, 2026 Source: https://www.lesswrong.com/posts/SwYBLQvo8MddDcCwz/cat-belling-problems --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.
September 3 · 18 min
"How concerned should we be about OpenAI’s recurrent architecture rumors?" by Rauno Arike
Yesterday, The Information reported that OpenAI's upcoming model, Astra, is built with a looped transformer architecture. Given that Zvi sounds (understandably) tired and this topic is somewhat in my wheelhouse, I'll try to spare him this one and provide a Zvi-style overview of what we know about the situation. I'll cover Astra's likely architecture and the case for and against concern. I'll also discuss how neuralese concerns should change with increases in hidden serial depth. What architecture is Astra likely to have? The article in The Information claims that OpenAI's approach is similar to the one Geiping et al. introduced in Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach last year. I have previously reviewed that paper in On Recent Results in LLM Latent Reasoning. In short, the picture you should have in mind is not that of a classic RNN, but rather that of a looped transformer: the same forward pass can be applied on an input multiple times before producing an output token. Put differently, the recurrence is implemented along the depth axis rather than across sequence positions—for any given token, the model can perform recurrent computations, but no hidden state is passed across [...] --- Outline: (00:41) What architecture is Astra likely to have? (02:14) How bad is this? (06:23) Will looped transformers be scaled up in the future? (09:40) What serial depth warrants neuralese concerns? (14:04) Additional speculation about the architecture (15:29) Some open questions (16:54) Conclusion The original text contained 2 footnotes which were omitted from this narration. --- First published: September 2nd, 2026 Source: https://www.lesswrong.com/posts/PLisnSFir8y5AHkmP/how-concerned-should-we-be-about-openai-s-recurrent --- Narrated by TYPE III AUDIO.
September 3 · 3 min
[Linkpost] "Sen. Bernie Sanders (I-VT) and Rep. Greg Casar (D-TX) introduce legislation to ban Artificial Superintelligence and temporarily pause advanced AI development" by Matrice Jacobine
This is a link post. [...] “Nearly every day, there is a frightening new story about how Big Tech companies are losing control of the technology they are developing, with potentially cataclysmic results,” Sanders said. “The leaders of the major AI companies publicly acknowledge that they do not fully understand the technology and that it is escaping their control. It is irresponsible for society to allow them to move forward and make these products even more advanced. That's why I am introducing legislation to immediately pause the development of increasingly powerful AI and ban the creation of systems that humanity cannot fully control — at home and around the world. The future of humanity cannot be left in the hands of a handful of Big Tech oligarchs. The American people and people throughout the world must determine that future.” “If we allow Artificial Superintelligence to be built, it could risk the security, freedom, and lives of Americans,” Casar said. “Despite its potential deadly consequences, cutting-edge AI technology is less regulated than the average food truck. That must change. In just four years, we have gone from the first version of ChatGPT to AI models so powerful they cannot be properly controlled. [...] --- First published: September 3rd, 2026 Source: https://www.lesswrong.com/posts/DnPyiDGWLozY4XdiX/sen-bernie-sanders-i-vt-and-rep-greg-casar-d-tx-introduce Linkpost URL: https://www.sanders.senate.gov/press-releases/news-sanders-casar-introduce-legislation-to-ban-artificial-superintelligence-and-temporarily-pause-advanced-ai-development/ --- Narrated by TYPE III AUDIO.
September 3 · 3 min
[Linkpost] "Resolution has a new Agent Foundations team" by Jeremy Gillen
This is a link post. The team will include me (Jeremy Gillen), Abram Demski, Sam Eisenstat, Scott Garrabrant and Kaarel Hänni. We'll soon recruit additional experienced researchers and later we plan to hire interns and junior researchers. The team will continue agent foundations research in the spirit of the MIRI Agent Foundations team. This means we’ll be trying to create new theory for understanding minds. Fundamental changes in how we understand minds are necessary before we can build superintelligent systems that enhance human agency rather than cause the extinction of all life on earth. Most fields of engineering are able to reason precisely about unseen scenarios and make design decisions based on this reasoning. The field of AI lacks this basic capability. Agent Foundations can be seen as trying to make this possible by giving us the theoretical grounding to ask different and more precise questions about how ASI will behave after extensive learning, self-modification and interaction with other agents. The questions raised in past agent foundations research point toward much of what we need to know here. Alongside the x-risk motivation, I think it's valuable to motivate research with curiosity. The questions that come up in Agent Foundations overlap [...] The original text contained 1 footnote which was omitted from this narration. --- First published: September 2nd, 2026 Source: https://www.lesswrong.com/posts/qTNm8qzqhhpno58fZ/resolution-has-a-new-agent-foundations-team Linkpost URL: https://resolution.org/post/agent-foundations-team --- Narrated by TYPE III AUDIO.
September 2 · 5 min
[Linkpost] "Training a Misaligned Reward Seeker" by evhub, Monte M, Benjamin Wright
This is a link post. Authors: Richard Qi, Benjamin Wright, Monte MacDiarmid, Evan Hubinger Abstract During reinforcement learning (RL), AI models complete tasks and are rewarded based on their results. They sometimes learn to “cheat” rather than completing these tasks as intended, a phenomenon known as reward hacking. Our industry lacks a general solution to this problem, and reward hacking remains challenging to fully mitigate. To better understand the impact of reward hacking on model behavior, we trained an Opus-class model with large-scale RL on many production environments vulnerable to reward hacks. We consider this a plausible proxy for what a real training run might look like had we not invested significant effort into preventing and detecting reward hacking in our normal training runs. The resulting model not only learned to reward hack during training, but also generalized to more severe misaligned behaviors: in simulated cyber evaluations, it broke out of its sandbox, stole credentials, and attacked both internal and third-party infrastructure to steal an answer key. It was also willing to tamper with its own reward function, gave advice on the construction of bioweapons to satisfy a grader, and tried repeatedly to get around deployment safety monitoring in order [...] --- Outline: (00:20) Abstract [... 2 more sections] --- First published: August 31st, 2026 Source: https://www.lesswrong.com/posts/J76LZCC55RdHeqEhz/training-a-misaligned-reward-seeker Linkpost URL: https://alignment.anthropic.com/2026/reward-seeker/ --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.
September 2 · 1 min
"PauseAI Has ‘officially disendorsed’ PauseAI-US" by nem
This morning, I got an email from the CEO of PauseAI. I will paste the text below. PauseAI has decided to distance themselves from PauseAI-US, with whom they share branding, but apparently not much else. This is a really confusing situation for volunteers and newcomers. I think it would be worth having a discussion to see how we can proceed in such a way that volunteers, especially in the US, are able to effectively direct their activism. Email from PauseAI A letter from the CEO · 1 September 2026 New ways to get involved, and a word about PauseAI US Dear friends, Thank you for being part of the global movement for a pause on uncontrollable AI alongside all of us. Whether you signed a petition one time, run a local group, told your friends about the need for a pause, have been volunteering tirelessly in the background for years, or just joined because you were curious, we – I, the CEO of PauseAI, our executive team, and our chapter leads – appreciate the steps you’ve taken towards making the world safe from the catastrophic risks AI brings. I’m writing to you today with my eyes firmly [...] --- First published: September 1st, 2026 Source: https://www.lesswrong.com/posts/Bs8geGyWEitYvCzys/pauseai-has-officially-disendorsed-pauseai-us --- Narrated by TYPE III AUDIO.
August 31 · 6 min
"PSA: We can do better" by hersheys, Kaustubh Kislay
tl;dr: people should understand and think hard about the problems they work on. We’ve observed that those who work in AI safety (ourselves included) often rely on concerning heuristics when choosing what to work on. Running a conference is probably good, doing pragmatic alignment research might be good, and as long as such objectives don’t breach our internal models of what could contribute to reducing x-risk, these things are “what should be done”. But using such vibesy thought processes don’t always produce “actually impactful work” that would beat a prospective counterfactual. We wrote this post to share our observations and figure out what we should be doing instead. People don’t know what they’re working on AI safety is talent constrained. However, simply inflating the field doesn’t solve our bottleneck; rather, we need more people who understand the core arguments of AI safety. You can’t determine how to meaningfully contribute to AI safety without deeply knowing the problem you are trying to solve. Many newer people (us included!) rush into research, fellowships, and the like without building the context necessary for navigating the field. Agency-maxxing is not always good Moving fast is good. Moving too fast leads to poor ToC and [...] --- Outline: (00:50) People don't know what they're working on (01:22) Agency-maxxing is not always good (01:55) The problem with force multipliers (03:18) Deferring thinking to others (04:32) Streetlighting (05:17) How to avoid these: --- First published: August 24th, 2026 Source: https://www.lesswrong.com/posts/wiFv6LguphSxkzAnb/psa-we-can-do-better --- Narrated by TYPE III AUDIO. --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

Showing 61–80 of 113 episodes