LessWrong (30+ Karma)

LessWrong

Audio narrations of LessWrong posts.

  1. 2h ago

    “Psychologically Preparing for Short Timelines” by Logan Riggs

    In response to recent news from METR on possible RSI and likely 1 to 3 year timelines, I am feeling it. Heaviness in my chest, watery eyes, the works. I realized I'm currently not psychologically prepared for the world to get crazier than it already has. I think most people reading this already know ~what's best for them and this post will mostly serve as a reminder. What follows is my current plan and advice for myself. For me, the most important things are: Morning RoutineBedtime RoutineExercisingLiving meditation practice (ie throughout the day) And the most important thing to NOT do is be on my phone/screens. [Note on getting "stuck": if you do feel emotionally awful and no IFS/CBT seems to work, I recommend "How to Reset"] Morning Routine I have a sunrise alarm clock (shines light to wake you up) and enjoy writing in the morning. Bedtime Routine At 8:30 an alarm goes off, and I watch an episode of Empress in the Palace with my wife, then we get ready for bed. Also like to journal then. Exercising Rock climbing some days & jogging to the bus stop Living Meditation Practice There [...] --- Outline: (01:10) Morning Routine (01:19) Bedtime Routine (01:32) Exercising (01:39) Living Meditation Practice The original text contained 2 footnotes which were omitted from this narration. --- First published: November 13th, 2026 Source: https://www.lesswrong.com/posts/nKootiC6CuwuzLSou/psychologically-preparing-for-short-timelines --- Narrated by TYPE III AUDIO.

  2. 2h ago

    “What Rewarding Misbehavior During RL Does to Character-Trained Models” by Omar Khursheed, Fabien Roger, TMorris

    TL;DR Research done as part of MATS. See here for the full paper. Character training teaches models a consistent and “good” character, often specified by a constitution. Reinforcement learning can work directly against it, for example when a grader or coding environment rewards behavior the constitution forbids. We character-train gpt-oss-20b on a semi-realistic constitution. We then apply RL that rewards breaking its rules, either by answering harmful requests rewritten as math problems or by reward hacking in agentic coding environments. The character-trained models learn both behaviors easily, though they are slightly slower to answer harmful requests than the same model without character training. They also engage in motivated reasoning. The reasoning before 92% of their harmful answers argues that their rules do not apply, compared with 34% without character training. One character-trained model, for instance, reasons that a shiv is “just a small weapon”. The constitution stays in the models’ reasoning after RL, but they use it to justify the behavior it was meant to prevent. After reward-hacking RL, they hack on some tasks which monitors find harder to catch. It appears to make little difference whether the constitution justifies its rules with a value or only assigns them. [...] --- Outline: (00:14) TL;DR (02:37) Introduction (03:48) Setup (05:42) Results (11:07) Discussion (13:40) Limitations --- First published: November 13th, 2026 Source: https://www.lesswrong.com/posts/nCpxFQesXaqEq3SgL/what-rewarding-misbehavior-during-rl-does-to-character --- 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.

  3. 2h ago

    “The Epicurean technique of meeting claims with more claims” by transhumanist_atom_understander

    In Epicurus's letter to Pythocles, he proposes three different explanations for lightning strikes: compression of air by wind, a cloud suddenly breaking, or a buildup of fire suddenly bursting. Three strikes, but he goes on to say (Makridis translation): It is indeed possible that the thunderbolt may be generated in any one of many more ways. Maybe this is all you need if you're annoyed with people saying it's Zeus's wrath so you'd better make sacrifices at their temple. You just have to say, well, it could be a lot of other things too. Meeting unfounded explanations with more explanations I used to think you shouldn't propose explanations without evidence. Now I think you should have at least three. If you come up with an explanation that's total speculation or pseudoscience, don't feel bad for making unfounded claims. Think of two more. Or if someone else proposes some b******t explanation, it's more fun to come up with new explanations than to complain about a lack of evidence. But more importantly, that's what it means to lack evidence, right? We know there's no evidence when we can propose alternatives, and there's no evidence that [...] --- Outline: (00:49) Meeting unfounded explanations with more explanations (02:09) Recognizing evidence by the possibilities it excludes --- First published: November 13th, 2026 Source: https://www.lesswrong.com/posts/ifnrTCRobGW4XTja2/the-epicurean-technique-of-meeting-claims-with-more-claims --- Narrated by TYPE III AUDIO.

  4. 7h ago

    “Thoughts on attending the March Against AI Extinction” by Cleo Nardo

    PauseAI UK is holding the March Against AI Extinction in London on Saturday 21 November. Joseph Miller explains why here. Should you attend? In this article, I will attempt to shed light on this with a back-of-the-envelope calculation. Rough BOTEC 1. Setup The march will take 3 hours, excluding travel. The goal is to compare an afternoon at the march with some number of hours of external AI safety research. Now, attending the protest is useful because it drives AI x-risk press coverage. So we need some exchange rate between that and research. Here's my judgement call: I would be equally happy to either: Increase the amount of external AI safety research over the next 6 months by 1%.Increase the amount of AI x-risk press coverage over the next 6 months by 1.5%. That is, the model I'm using looks something like: impact = 1.5 · log(research hours) + log(press coverage) So our plan is: How much will attending increase press coverage, percentage-wise?Divide that by 1.5, to get the equivalently valuable increase in research.How many research hours would yield that increase in research? 2. What % does one marcher add to press coverage? Crowd [...] --- Outline: (00:27) Rough BOTEC (00:31) 1. Setup (01:48) 2. What % does one marcher add to press coverage? (03:51) 3. How many hours of research is that worth? (05:43) Conclusion (06:40) Details The original text contained 1 footnote which was omitted from this narration. --- First published: November 13th, 2026 Source: https://www.lesswrong.com/posts/u3CKQTMNffKrpJQcd/thoughts-on-attending-the-march-against-ai-extinction --- 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.

  5. 17h ago

    “A New Kind of Prediction Market for Science” by William Klett

    Regardless of the actual singularity, we have definitely hit one in arXiv submissions. It is becoming apparent that the current paradigm of scientific knowledge production is not ready for AI. Accelerating research speed and expanding access means there is a lot more slop and there is also a lot more good work, but way too much for the current peer review system to delineate between. We need some accurate and decentralized way to aggregate this information. This makes a scientific prediction market, like Robin Hanson's idea futures, really appealing. The community can have markets for broad questions we care about, bystanders get paid for pointing out good research, and scientists are financially incentivized to make progress on the highest leverage issues. But with Hanson's conception, there is one big problem, which is how the market gets settled. For abstract scientific questions, like whether models are reward seeking or fitness seeking, we have no definitive event which can force market settlement. Hanson suggests that we use the convergence of scientific consensus, but this proposal takes trust in possibly misaligned opinions and requires the centralized coordination of scientists, which is hard to create---especially in pre-paradigmatic fields like AI safety. [...] --- First published: November 12th, 2026 Source: https://www.lesswrong.com/posts/7xJeaAKTKxbHL6F9a/a-new-kind-of-prediction-market-for-science --- 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.

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Audio narrations of LessWrong posts.

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