“Lack of Social Grace is a Lack of Skill” by Screwtape

1.  I have claimed that one of the fundamental questions of rationality is “what am I about to do and what will happen next?” One of the domains I ask this question the most is in social situations. There are a great many skills in the world. If I had the time and resources to do so, I’d want to master all of them. Wilderness survival, automotive repair, the Japanese language, calculus, heart surgery, French cooking, sailing, underwater basket weaving, architecture, Mexican cooking, functional programming, whatever it is people mean when they say “hey man, just let him cook.” My inability to speak fluent Japanese isn’t a sin or a crime. However, it isn’t a virtue either; If I had the option to snap my fingers and instantly acquire the knowledge, I’d do it. Now, there's a different question of prioritization; I tend to pick new skills to learn by a combination of what's useful to me, what sounds fun, and what I’m naturally good at. I picked up the basics of computer programming easily, I enjoy doing it, and it turned out to pay really well. That was an over-determined skill to learn. On the other [...] ---Outline:(00:10) 1.(03:42) 2.(06:44) 3. The original text contained 2 footnotes which were omitted from this narration. --- First published: November 3rd, 2025 Source: https://www.lesswrong.com/posts/NnTwbvvsPg5kj3BKq/lack-of-social-grace-is-a-lack-of-skill-1 --- Narrated by TYPE III AUDIO. ---Images from the article:Apple Podcasts and Spotify do not show images

This is a link post. Eliezer Yudkowsky did not exactly suggest that you should eat bear fat covered with honey and sprinkled with salt flakes. What he actually said was that an alien, looking from the outside at evolution, would predict that you would want to eat bear fat covered with honey and sprinkled with salt flakes. Still, I decided to buy a jar of bear fat online, and make a treat for the people at Inkhaven. It was surprisingly good. My post discusses how that happened, and a bit about the implications for Eliezer's thesis. Let me know if you want to try some; I can prepare some for you if you happen to be at Lighthaven before we run out of bear fat, and before I leave toward the end of November. --- First published: November 4th, 2025 Source: https://www.lesswrong.com/posts/2pKiXR6X7wdt8eFX5/i-ate-bear-fat-with-honey-and-salt-flakes-to-prove-a-point Linkpost URL:https://signoregalilei.com/2025/11/03/i-ate-bear-fat-to-prove-a-point/ --- Narrated by TYPE III AUDIO.

As far as I'm aware, Anthropic is the only AI company with official AGI timelines[1]: they expect AGI by early 2027. In their recommendations (from March 2025) to the OSTP for the AI action plan they say: As our CEO Dario Amodei writes in 'Machines of Loving Grace', we expect powerful AI systems will emerge in late 2026 or early 2027. Powerful AI systems will have the following properties: Intellectual capabilities matching or exceeding that of Nobel Prize winners across most disciplines—including biology, computer science, mathematics, and engineering. [...] They often describe this capability level as a "country of geniuses in a datacenter". This prediction is repeated elsewhere and Jack Clark confirms that something like this remains Anthropic's view (as of September 2025). Of course, just because this is Anthropic's official prediction[2] doesn't mean that all or even most employees at Anthropic share the same view.[3] However, I do think we can reasonably say that Dario Amodei, Jack Clark, and Anthropic itself are all making this prediction.[4] I think the creation of transformatively powerful AI systems—systems as capable or more capable than Anthropic's notion of powerful AI—is plausible in 5 years [...] ---Outline:(02:27) What does powerful AI mean?(08:40) Earlier predictions(11:19) A proposed timeline that Anthropic might expect(19:10) Why powerful AI by early 2027 seems unlikely to me(19:37) Trends indicate longer(21:48) My rebuttals to arguments that trend extrapolations will underestimate progress(26:14) Naively trend extrapolating to full automation of engineering and then expecting powerful AI just after this is probably too aggressive(30:08) What I expect(32:12) What updates should we make in 2026?(32:17) If something like my median expectation for 2026 happens(34:07) If something like the proposed timeline (with powerful AI in March 2027) happens through June 2026(35:25) If AI progress looks substantially slower than what I expect(36:09) If AI progress is substantially faster than I expect, but slower than the proposed timeline (with powerful AI in March 2027)(36:51) Appendix: deriving a timeline consistent with Anthropics predictions The original text contained 94 footnotes which were omitted from this narration. --- First published: November 3rd, 2025 Source: https://www.lesswrong.com/posts/gabPgK9e83QrmcvbK/what-s-up-with-anthropic-predicting-agi-by-early-2027-1 --- Narrated by TYPE III AUDIO. ---Images from the article:

This is a link post. New Anthropic research (tweet, blog post, paper): We investigate whether large language models can introspect on their internal states. It is difficult to answer this question through conversation alone, as genuine introspection cannot be distinguished from confabulations. Here, we address this challenge by injecting representations of known concepts into a model's activations, and measuring the influence of these manipulations on the model's self-reported states. We find that models can, in certain scenarios, notice the presence of injected concepts and accurately identify them. Models demonstrate some ability to recall prior internal representations and distinguish them from raw text inputs. Strikingly, we find that some models can use their ability to recall prior intentions in order to distinguish their own outputs from artificial prefills. In all these experiments, Claude Opus 4 and 4.1, the most capable models we tested, generally demonstrate the greatest introspective awareness; however, trends across models are complex and sensitive to post-training strategies. Finally, we explore whether models can explicitly control their internal representations, finding that models can modulate their activations when instructed or incentivized to “think about” a concept. Overall, our results indicate that current language models possess some functional introspective awareness [...] --- First published: October 30th, 2025 Source: https://www.lesswrong.com/posts/QKm4hBqaBAsxabZWL/emergent-introspective-awareness-in-large-language-models Linkpost URL:https://transformer-circuits.pub/2025/introspection/index.html --- 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.

This is a link post. You have things you want to do, but there's just never time. Maybe you want to find someone to have kids with, or maybe you want to spend more or higher-quality time with the family you already have. Maybe it's a work project. Maybe you have a musical instrument or some sports equipment gathering dust in a closet, or there's something you loved doing when you were younger that you want to get back into. Whatever it is, you can’t find the time for it. And yet you somehow find thousands of hours a year to watch YouTube, check Twitter and Instagram, listen to podcasts, binge Netflix shows, and read blogs and news articles. You can’t focus. You haven’t read a physical book in years, and the time you tried it was boring and you felt itchy and you think maybe books are outdated when there's so much to read on the internet anyway. You’re talking with a friend, but then your phone buzzes and you look at the notification and you open it, and your girlfriend has messaged you and that's nice, and then your friend says “Did you hear what I just said?” [...] --- First published: November 1st, 2025 Source: https://www.lesswrong.com/posts/6p4kv8uxYvLcimGGi/you-re-always-stressed-your-mind-is-always-busy-you-never Linkpost URL:https://mingyuan.substack.com/p/youre-always-stressed-your-mind-is --- Narrated by TYPE III AUDIO.

Crosspost from my blog. Synopsis When we share words with each other, we don't only care about the words themselves. We care also—even primarily—about the mental elements of the human mind/agency that produced the words. What we want to engage with is those mental elements. As of 2025, LLM text does not have those elements behind it. Therefore LLM text categorically does not serve the role for communication that is served by real text. Therefore the norm should be that you don't share LLM text as if someone wrote it. And, it is inadvisable to read LLM text that someone else shares as though someone wrote it. Introduction One might think that text screens off thought. Suppose two people follow different thought processes, but then they produce and publish identical texts. Then you read those texts. How could it possibly matter what the thought processes were? All you interact with is the text, so logically, if the two texts are the same then their effects on you are the same. But, a bit similarly to how high-level actions don’t screen off intent, text does not screen off thought. How [...] ---Outline:(00:13) Synopsis(00:57) Introduction(02:51) Elaborations(02:54) Communication is for hearing from minds(05:21) Communication is for hearing assertions(12:36) Assertions live in dialogue --- First published: November 1st, 2025 Source: https://www.lesswrong.com/posts/DDG2Tf2sqc8rTWRk3/llm-generated-text-is-not-testimony --- Narrated by TYPE III AUDIO.

An Overture Famously, trans people tend not to have great introspective clarity into their own motivations for transition. Intuitively, they tend to be quite aware of what they do and don't like about inhabiting their chosen bodies and gender roles. But when it comes to explaining the origins and intensity of those preferences, they almost universally to come up short. I've even seen several smart, thoughtful trans people, such as Natalie Wynn, making statements to the effect that it's impossible to develop a satisfying theory of aberrant gender identities. (She may have been exaggerating for effect, but it was clear she'd given up on solving the puzzle herself.) I'm trans myself, but even I can admit that this lack of introspective clarity is a reason to be wary of transgenderism as a phenomenon. After all, there are two main explanations for trans people's failure to thoroughly explain their own existence. One is that transgenderism is the result of an obscenely complex and arcane neuro-psychological phenomenon, which we have no hope of unraveling through normal introspective methods. The other is that trans people are lying about something, including to themselves. Now, a priori, both of these do seem like real [...] ---Outline:(00:12) An Overture(04:55) In the Case of Fiora Starlight(16:51) Was it worth it? The original text contained 3 footnotes which were omitted from this narration. --- First published: November 1st, 2025 Source: https://www.lesswrong.com/posts/gEETjfjm3eCkJKesz/post-title-why-i-transitioned-a-case-study --- 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.

TL;DR: AI progress and the recognition of associated risks are painful to think about. This cognitive dissonance acts as fertile ground in the memetic landscape, a high-energy state that will be exploited by novel ideologies. We can anticipate cultural evolution will find viable successionist ideologies: memeplexes that resolve this tension by framing the replacement of humanity by AI not as a catastrophe, but as some combination of desirable, heroic, or inevitable outcome. This post mostly examines the mechanics of the process. Most analyses of ideologies fixate on their specific claims - what acts are good, whether AIs are conscious, whether Christ is divine, or whether Virgin Mary was free of original sin from the moment of her conception. Other analyses focus on exegeting individual thinkers: 'What did Marx really mean?' In this text, I'm trying to do something different - mostly, look at ideologies from an evolutionary perspective. I [...] ---Outline:(01:27) What Makes Memes Fit?(03:30) The Cultural Evolution Search Process(04:31) The Fertile Ground: Sources of Dissonance(04:53) 1. The Builders Dilemma and the Hero Narrative(05:35) 2. The Sadness of Obsolescence(06:06) 3. X-Risk(06:24) 4. The Wrong Side of History(06:36) 5. The Progress Heuristic(06:57) The Resulting Pressure(07:52) The Meme Pool: Raw Materials for Successionism(08:14) 1. Devaluing Humanity(09:10) 2. Legitimizing the Successor AI(12:08) 3. Narratives of Inevitability(12:13) Memes that make our obsolescence seem like destiny rather than defeat.(14:14) Novel Factor: the AIs(16:05) Defense Against Becoming a Host(18:13) Appendix: Some memes --- First published: October 28th, 2025 Source: https://www.lesswrong.com/posts/XFDjzKXZqKdvZ2QKL/the-memetics-of-ai-successionism --- Narrated by TYPE III AUDIO.

This is the latest in a series of essays on AI Scaling. You can find the others on my site. Summary: RL-training for LLMs scales surprisingly poorly. Most of its gains are from allowing LLMs to productively use longer chains of thought, allowing them to think longer about a problem. There is some improvement for a fixed length of answer, but not enough to drive AI progress. Given the scaling up of pre-training compute also stalled, we'll see less AI progress via compute scaling than you might have thought, and more of it will come from inference scaling (which has different effects on the world). That lengthens timelines and affects strategies for AI governance and safety. The current era of improving AI capabilities using reinforcement learning (from verifiable rewards) involves two key types of scaling: Scaling the amount of compute used for RL during training Scaling [...] ---Outline:(09:46) How do these compare to pre-training scaling?(14:16) Conclusion --- First published: October 22nd, 2025 Source: https://www.lesswrong.com/posts/xpj6KhDM9bJybdnEe/how-well-does-rl-scale --- Narrated by TYPE III AUDIO. ---Images from the article:

I've created a highly specific and actionable privacy guide, sorted by importance and venturing several layers deep into the privacy iceberg. I start with the basics (password manager) but also cover the obscure (dodging the millions of Bluetooth tracking beacons which extend from stores to traffic lights; anti-stingray settings; flashing GrapheneOS on a Pixel). I feel strongly motivated by current events, but the guide also contains a large amount of timeless technical content. Here's a preview. Digital Threat Modeling Under Authoritarianism by Bruce Schneier Being innocent won't protect you. This is vital to understand. Surveillance systems and sorting algorithms make mistakes. This is apparent in the fact that we are routinely served advertisements for products that don’t interest us at all. Those mistakes are relatively harmless—who cares about a poorly targeted ad?—but a similar mistake at an immigration hearing can get someone deported. An authoritarian government doesn't care. Mistakes are a feature and not a bug of authoritarian surveillance. If ICE targets only people it can go after legally, then everyone knows whether or not they need to fear ICE. If ICE occasionally makes mistakes by arresting Americans and deporting innocents, then everyone has to [...] ---Outline:(01:55) What should I read?(02:53) Whats your risk level?(03:46) What information this guide will and wont help you protect(05:00) Overview of the technical recommendations in each post(05:05) Privacy Despite Authoritarianism(06:08) Advanced Privacy Despite Authoritarianism --- First published: October 29th, 2025 Source: https://www.lesswrong.com/posts/BPyieRshykmrdY36A/an-opinionated-guide-to-privacy-despite-authoritarianism --- 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.