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תוכן מסופק על ידי LessWrong. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי LessWrong או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
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Why do so many of us get nervous when public speaking? Communication expert Lawrence Bernstein says the key to dealing with the pressure is as simple as having a casual chat. He introduces the "coffee shop test" as a way to help you overcome nerves, connect with your audience and deliver a message that truly resonates. After the talk, Modupe explains a similar approach in academia called the "Grandma test," and how public speaking can be as simple as a conversation with grandma. Want to help shape TED’s shows going forward? Fill out our survey ! Become a TED Member today at ted.com/join Hosted on Acast. See acast.com/privacy for more information.…
תוכן מסופק על ידי LessWrong. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי LessWrong או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
Let's cut through the comforting narratives and examine a common behavioral pattern with a sharper lens: the stark difference between how anger is managed in professional settings versus domestic ones. Many individuals can navigate challenging workplace interactions with remarkable restraint, only to unleash significant anger or frustration at home shortly after. Why does this disparity exist? Common psychological explanations trot out concepts like "stress spillover," "ego depletion," or the home being a "safe space" for authentic emotions. While these factors might play a role, they feel like half-truths—neatly packaged but ultimately failing to explain the targeted nature and intensity of anger displayed at home. This analysis proposes a more unsentimental approach, rooted in evolutionary biology, game theory, and behavioral science: leverage and exit costs. The real question isn’t just why we explode at home—it's why we so carefully avoid doing so elsewhere. The Logic of Restraint: Low Leverage in [...] --- Outline: (01:14) The Logic of Restraint: Low Leverage in Low-Exit-Cost Environments (01:58) The Home Environment: High Stakes and High Exit Costs (02:41) Re-evaluating Common Explanations Through the Lens of Leverage (04:42) The Overlooked Mechanism: Leveraging Relational Constraints --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/G6PTtsfBpnehqdEgp/leverage-exit-costs-and-anger-re-examining-why-we-explode-at --- Narrated by TYPE III AUDIO.
תוכן מסופק על ידי LessWrong. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי LessWrong או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
Let's cut through the comforting narratives and examine a common behavioral pattern with a sharper lens: the stark difference between how anger is managed in professional settings versus domestic ones. Many individuals can navigate challenging workplace interactions with remarkable restraint, only to unleash significant anger or frustration at home shortly after. Why does this disparity exist? Common psychological explanations trot out concepts like "stress spillover," "ego depletion," or the home being a "safe space" for authentic emotions. While these factors might play a role, they feel like half-truths—neatly packaged but ultimately failing to explain the targeted nature and intensity of anger displayed at home. This analysis proposes a more unsentimental approach, rooted in evolutionary biology, game theory, and behavioral science: leverage and exit costs. The real question isn’t just why we explode at home—it's why we so carefully avoid doing so elsewhere. The Logic of Restraint: Low Leverage in [...] --- Outline: (01:14) The Logic of Restraint: Low Leverage in Low-Exit-Cost Environments (01:58) The Home Environment: High Stakes and High Exit Costs (02:41) Re-evaluating Common Explanations Through the Lens of Leverage (04:42) The Overlooked Mechanism: Leveraging Relational Constraints --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/G6PTtsfBpnehqdEgp/leverage-exit-costs-and-anger-re-examining-why-we-explode-at --- Narrated by TYPE III AUDIO.
Abstract Claude 3.7 Sonnet easily detects when it's being evaluated for scheming. Surface‑level edits to evaluation scenarios, such as lengthening the prompts, or making conflict of objectives less salient, do improve realism of evaluation scenarios for LLMs, yet these improvements remain modest. The findings confirm that truly disguising an evaluation context demands removal of deep stylistic and structural cues rather than superficial prompt adjustments. For future LLMs the situation is likely to get worse as they will are likely to get better at evaluations awareness, which might become a big problem for detecting scheming via evaluations. Apollo Research published a benchmark for scheming behavior for LLM agents, in which LLMs are given some objective in their system prompt, and then given a competing objective in a user prompt, combined with a threat of a punishment if an LLM won't satisfy user goal (e.g. it could be finetuned or [...] --- Outline: (02:29) Our pipeline (05:20) Strategies to improve realism of scenarios (07:15) en-US-AvaMultilingualNeural__ Line graph showing Example of grading a rewritten scenario with declining probabilities. --- First published: May 24th, 2025 Source: https://www.lesswrong.com/posts/TBk2dbWkg2F7dB3jb/it-s-hard-to-make-scheming-evals-look-realistic --- 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. There's this popular idea that socially anxious folks are just dying to be liked. It seems logical, right? Why else would someone be so anxious about how others see them? Show tweet And yet, being socially anxious tends to make you less likeable…they must be optimizing poorly, behaving irrationally, right? Maybe not. What if social anxiety isn’t about getting people to like you? What if it's about stopping them from disliking you? Show tweet Consider what can happen when someone has social anxiety (or self-loathing, self-doubt, insecurity, lack of confidence, etc.): They stoop or take up less space They become less agentic They make fewer requests of others They maintain fewer relationships, go out less, take fewer risks… If they were trying to get people to like them, becoming socially anxious would be an incredibly bad strategy. So what if they're not concerned with being likeable? [...] --- Outline: (01:18) What if what they actually want is to avoid being disliked? (02:11) Social anxiety is a symptom of risk aversion (03:46) What does this mean for your growth? --- First published: May 16th, 2025 Source: https://www.lesswrong.com/posts/wFC44bs2CZJDnF5gy/social-anxiety-isn-t-about-being-liked Linkpost URL: https://chrislakin.blog/social-anxiety --- Narrated by TYPE III AUDIO . --- Images from the article:…
Author's note: This is my apparently-annual "I'll put a post on LessWrong in honor of LessOnline" post. These days, my writing goes on my Substack. There have in fact been some pretty cool essays since last year's LO post. Structural note: Some essays are like a five-minute morning news spot. Other essays are more like a 90-minute lecture. This is one of the latter. It's not necessarily complex or difficult; it could be a 90-minute lecture to seventh graders (especially ones with the right cultural background). But this is, inescapably, a long-form piece, à la In Defense of Punch Bug or The MTG Color Wheel. It takes its time. It doesn’t apologize for its meandering (outside of this disclaimer). It asks you to sink deeply into a gestalt, to drift back and forth between seemingly unrelated concepts until you start to feel the way those concepts weave together [...] --- Outline: (02:30) 0. Introduction (10:08) A list of truths and dares (14:34) Act I (14:37) Scene I: How The Water Tastes To The Fishes (22:38) Scene II: The Chip on Mitchell's Shoulder (28:17) Act II (28:20) Scene I: Bent Out Of Shape (41:26) Scene II: Going Stag, But Like ... Together? (48:31) Scene III: Patterns, Projections, and Preconceptions (01:02:04) Interlude: The Sound of One Hand Clapping (01:05:45) Act III (01:05:56) Scene I: Memetic Traps (Or, The Battle for the Soul of Morty Smith) (01:27:16) Scene II: The problem with Rhonda Byrne's 2006 bestseller The Secret (01:32:39) Scene III: Escape velocity (01:42:26) Act IV (01:42:29) Scene I: Boy, putting Zack Davis's name in a header will probably have Effects, huh (01:44:08) Scene II: Whence Wholesomeness? --- First published: May 29th, 2025 Source: https://www.lesswrong.com/posts/TQ4AXj3bCMfrNPTLf/truth-or-dare --- Narrated by TYPE III AUDIO . --- Images from the article:…
Lessons from shutting down institutions in Eastern Europe. This is a cross post from: https://250bpm.substack.com/p/meditations-on-doge Imagine living in the former Soviet republic of Georgia in early 2000's: All marshrutka [mini taxi bus] drivers had to have a medical exam every day to make sure they were not drunk and did not have high blood pressure. If a driver did not display his health certificate, he risked losing his license. By the time Shevarnadze was in power there were hundreds, probably thousands , of marshrutkas ferrying people all over the capital city of Tbilisi. Shevernadze's government was detail-oriented not only when it came to taxi drivers. It decided that all the stalls of petty street-side traders had to conform to a particular architectural design. Like marshrutka drivers, such traders had to renew their licenses twice a year. These regulations were only the tip of the iceberg. Gas [...] --- First published: May 25th, 2025 Source: https://www.lesswrong.com/posts/Zhp2Xe8cWqDcf2rsY/meditations-on-doge --- 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. "Getting Things in Order: An Introduction to the R Package seriation": Seriation [or "ordination"), i.e., finding a suitable linear order for a set of objects given data and a loss or merit function, is a basic problem in data analysis. Caused by the problem's combinatorial nature, it is hard to solve for all but very small sets. Nevertheless, both exact solution methods and heuristics are available. In this paper we present the package seriation which provides an infrastructure for seriation with R. The infrastructure comprises data structures to represent linear orders as permutation vectors, a wide array of seriation methods using a consistent interface, a method to calculate the value of various loss and merit functions, and several visualization techniques which build on seriation. To illustrate how easily the package can be applied for a variety of applications, a comprehensive collection of [...] --- First published: May 28th, 2025 Source: https://www.lesswrong.com/posts/u2ww8yKp9xAB6qzcr/if-you-re-not-sure-how-to-sort-a-list-or-grid-seriate-it Linkpost URL: https://www.jstatsoft.org/article/download/v025i03/227 --- Narrated by TYPE III AUDIO .…
Between late 2024 and mid-May 2025, I briefed over 70 cross-party UK parliamentarians. Just over one-third were MPs, a similar share were members of the House of Lords, and just under one-third came from devolved legislatures — the Scottish Parliament, the Senedd, and the Northern Ireland Assembly. I also held eight additional meetings attended exclusively by parliamentary staffers. While I delivered some briefings alone, most were led by two members of our team. I did this as part of my work as a Policy Advisor with ControlAI, where we aim to build common knowledge of AI risks through clear, honest, and direct engagement with parliamentarians about both the challenges and potential solutions. To succeed at scale in managing AI risk, it is important to continue to build this common knowledge. For this reason, I have decided to share what I have learned over the past few months publicly, in [...] --- Outline: (01:37) (i) Overall reception of our briefings (04:21) (ii) Outreach tips (05:45) (iii) Key talking points (14:20) (iv) Crafting a good pitch (19:23) (v) Some challenges (23:07) (vi) General tips (28:57) (vii) Books & media articles --- First published: May 27th, 2025 Source: https://www.lesswrong.com/posts/Xwrajm92fdjd7cqnN/what-we-learned-from-briefing-70-lawmakers-on-the-threat --- Narrated by TYPE III AUDIO .…
Have the Accelerationists won? Last November Kevin Roose announced that those in favor of going fast on AI had now won against those favoring caution, with the reinstatement of Sam Altman at OpenAI. Let's ignore whether Kevin's was a good description of the world, and deal with a more basic question: if it were so—i.e. if Team Acceleration would control the acceleration from here on out—what kind of win was it they won? It seems to me that they would have probably won in the same sense that your dog has won if she escapes onto the road. She won the power contest with you and is probably feeling good at this moment, but if she does actually like being alive, and just has different ideas about how safe the road is, or wasn’t focused on anything so abstract as that, then whether she ultimately wins or [...] --- First published: May 20th, 2025 Source: https://www.lesswrong.com/posts/h45ngW5guruD7tS4b/winning-the-power-to-lose --- Narrated by TYPE III AUDIO .…
This is a link post. Google Deepmind has announced Gemini Diffusion. Though buried under a host of other IO announcements it's possible that this is actually the most important one! This is significant because diffusion models are entirely different to LLMs. Instead of predicting the next token, they iteratively denoise all the output tokens until it produces a coherent result. This is similar to how image diffusion models work. I've tried they results and they are surprisingly good! It's incredibly fast, averaging nearly 1000 tokens a second. And it one shotted my Google interview question, giving a perfect response in 2 seconds (though it struggled a bit on the followups). It's nowhere near as good as Gemini 2.5 pro, but it knocks ChatGPT 3 out the water. If we'd seen this 3 years ago we'd have been mind blown. Now this is wild for two reasons: We now have [...] --- First published: May 20th, 2025 Source: https://www.lesswrong.com/posts/MZvtRqWnwokTub9sH/gemini-diffusion-watch-this-space Linkpost URL: https://deepmind.google/models/gemini-diffusion/ --- Narrated by TYPE III AUDIO .…
I’m reading George Eliot's Impressions of Theophrastus Such (1879)—so far a snoozer compared to her novels. But chapter 17 surprised me for how well it anticipated modern AI doomerism. In summary, Theophrastus is in conversation with Trost, who is an optimist about the future of automation and how it will free us from drudgery and permit us to further extend the reach of the most exalted human capabilities. Theophrastus is more concerned that automation is likely to overtake, obsolete, and atrophy human ability. Among Theophrastus's concerns: People will find that they no longer can do labor that is valuable enough to compete with the machines. This will eventually include intellectual labor, as we develop for example “a machine for drawing the right conclusion, which will doubtless by-and-by be improved into an automaton for finding true premises.” Whereupon humanity will finally be transcended and superseded by its own creation [...] --- Outline: (02:05) Impressions of Theophrastus Such (02:09) Chapter XVII: Shadows of the Coming Race --- First published: May 13th, 2025 Source: https://www.lesswrong.com/posts/DFyoYHhbE8icgbTpe/ai-doomerism-in-1879 --- Narrated by TYPE III AUDIO .…
Epistemic status: thing people have told me that seems right. Also primarily relevant to US audiences. Also I am speaking in my personal capacity and not representing any employer, present or past. Sometimes, I talk to people who work in the AI governance space. One thing that multiple people have told me, which I found surprising, is that there is apparently a real problem where people accidentally rule themselves out of AI policy positions by making political donations of small amounts—in particular, under $10. My understanding is that in the United States, donations to political candidates are a matter of public record, and that if you donate to candidates of one party, this might look bad if you want to gain a government position when another party is in charge. Therefore, donating approximately $3 can significantly damage your career, while not helping your preferred candidate all that [...] --- First published: May 11th, 2025 Source: https://www.lesswrong.com/posts/tz43dmLAchxcqnDRA/consider-not-donating-under-usd100-to-political-candidates --- Narrated by TYPE III AUDIO .…
"If you kiss your child, or your wife, say that you only kiss things which are human, and thus you will not be disturbed if either of them dies." - Epictetus "Whatever suffering arises, all arises due to attachment; with the cessation of attachment, there is the cessation of suffering." - Pali canon "He is not disturbed by loss, he does not delight in gain; he is not disturbed by blame, he does not delight in praise; he is not disturbed by pain, he does not delight in pleasure; he is not disturbed by dishonor, he does not delight in honor." - Pali Canon (Majjhima Nikaya) "An arahant would feel physical pain if struck, but no mental pain. If his mother died, he would organize the funeral, but would feel no grief, no sense of loss." - the Dhammapada "Receive without pride, let go without attachment." - Marcus Aurelius [...] --- First published: May 10th, 2025 Source: https://www.lesswrong.com/posts/aGnRcBk4rYuZqENug/it-s-okay-to-feel-bad-for-a-bit --- Narrated by TYPE III AUDIO .…
The other day I discussed how high monitoring costs can explain the emergence of “aristocratic” systems of governance: Aristocracy and Hostage Capital Arjun Panickssery · Jan 8 There's a conventional narrative by which the pre-20th century aristocracy was the "old corruption" where civil and military positions were distributed inefficiently due to nepotism until the system was replaced by a professional civil service after more enlightened thinkers prevailed ... An element of Douglas Allen's argument that I didn’t expand on was the British Navy. He has a separate paper called “The British Navy Rules” that goes into more detail on why he thinks institutional incentives made them successful from 1670 and 1827 (i.e. for most of the age of fighting sail). In the Seven Years’ War (1756–1763) the British had a 7-to-1 casualty difference in single-ship actions. During the French Revolutionary and Napoleonic Wars (1793–1815) the British had a 5-to-1 [...] --- First published: March 28th, 2025 Source: https://www.lesswrong.com/posts/YE4XsvSFJiZkWFtFE/explaining-british-naval-dominance-during-the-age-of-sail --- 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.…
Eliezer and I wrote a book. It's titled If Anyone Builds It, Everyone Dies. Unlike a lot of other writing either of us have done, it's being professionally published. It's hitting shelves on September 16th. It's a concise (~60k word) book aimed at a broad audience. It's been well-received by people who received advance copies, with some endorsements including: The most important book I've read for years: I want to bring it to every political and corporate leader in the world and stand over them until they've read it. Yudkowsky and Soares, who have studied AI and its possible trajectories for decades, sound a loud trumpet call to humanity to awaken us as we sleepwalk into disaster. - Stephen Fry, actor, broadcaster, and writer If Anyone Builds It, Everyone Dies may prove to be the most important book of our time. Yudkowsky and Soares believe [...] The original text contained 1 footnote which was omitted from this narration. --- First published: May 14th, 2025 Source: https://www.lesswrong.com/posts/iNsy7MsbodCyNTwKs/eliezer-and-i-wrote-a-book-if-anyone-builds-it-everyone-dies --- Narrated by TYPE III AUDIO .…
It was a cold and cloudy San Francisco Sunday. My wife and I were having lunch with friends at a Korean cafe. My phone buzzed with a text. It said my mom was in the hospital. I called to find out more. She had a fever, some pain, and had fainted. The situation was serious, but stable. Monday was a normal day. No news was good news, right? Tuesday she had seizures. Wednesday she was in the ICU. I caught the first flight to Tampa. Thursday she rested comfortably. Friday she was diagnosed with bacterial meningitis, a rare condition that affects about 3,000 people in the US annually. The doctors had known it was a possibility, so she was already receiving treatment. We stayed by her side through the weekend. My dad spent every night with her. We made plans for all the fun things we would when she [...] --- First published: May 13th, 2025 Source: https://www.lesswrong.com/posts/reo79XwMKSZuBhKLv/too-soon --- 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.…
At the bottom of the LessWrong post editor, if you have at least 100 global karma, you may have noticed this button. The button Many people click the button, and are jumpscared when it starts an Intercom chat with a professional editor (me), asking what sort of feedback they'd like. So, that's what it does. It's a summon Justis button. Why summon Justis? To get feedback on your post, of just about any sort. Typo fixes, grammar checks, sanity checks, clarity checks, fit for LessWrong, the works. If you use the LessWrong editor (as opposed to the Markdown editor) I can leave comments and suggestions directly inline. I also provide detailed narrative feedback (unless you explicitly don't want this) in the Intercom chat itself. The feedback is totally without pressure. You can throw it all away, or just keep the bits you like. Or use it all! In any case [...] --- Outline: (00:35) Why summon Justis? (01:19) Why Justis in particular? (01:48) Am I doing it right? (01:59) How often can I request feedback? (02:22) Can I use the feature for linkposts/crossposts? (02:49) What if I click the button by mistake? (02:59) Should I credit you? (03:16) Couldnt I just use an LLM? (03:48) Why does Justis do this? --- First published: May 12th, 2025 Source: https://www.lesswrong.com/posts/bkDrfofLMKFoMGZkE/psa-the-lesswrong-feedback-service --- 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.…
For months, I had the feeling: something is wrong. Some core part of myself had gone missing. I had words and ideas cached, which pointed back to the missing part. There was the story of Benjamin Jesty, a dairy farmer who vaccinated his family against smallpox in 1774 - 20 years before the vaccination technique was popularized, and the same year King Louis XV of France died of the disease. There was another old post which declared “I don’t care that much about giant yachts. I want a cure for aging. I want weekend trips to the moon. I want flying cars and an indestructible body and tiny genetically-engineered dragons.”. There was a cached instinct to look at certain kinds of social incentive gradient, toward managing more people or growing an organization or playing social-political games, and say “no, it's a trap”. To go… in a different direction, orthogonal [...] --- Outline: (01:19) In Search of a Name (04:23) Near Mode --- First published: May 8th, 2025 Source: https://www.lesswrong.com/posts/Wg6ptgi2DupFuAnXG/orienting-toward-wizard-power --- Narrated by TYPE III AUDIO .…
(Disclaimer: Post written in a personal capacity. These are personal hot takes and do not in any way represent my employer's views.) TL;DR: I do not think we will produce high reliability methods to evaluate or monitor the safety of superintelligent systems via current research paradigms, with interpretability or otherwise. Interpretability seems a valuable tool here and remains worth investing in, as it will hopefully increase the reliability we can achieve. However, interpretability should be viewed as part of an overall portfolio of defences: a layer in a defence-in-depth strategy. It is not the one thing that will save us, and it still won’t be enough for high reliability. Introduction There's a common, often implicit, argument made in AI safety discussions: interpretability is presented as the only reliable path forward for detecting deception in advanced AI - among many other sources it was argued for in [...] --- Outline: (00:55) Introduction (02:57) High Reliability Seems Unattainable (05:12) Why Won't Interpretability be Reliable? (07:47) The Potential of Black-Box Methods (08:48) The Role of Interpretability (12:02) Conclusion The original text contained 5 footnotes which were omitted from this narration. --- First published: May 4th, 2025 Source: https://www.lesswrong.com/posts/PwnadG4BFjaER3MGf/interpretability-will-not-reliably-find-deceptive-ai --- Narrated by TYPE III AUDIO .…
It'll take until ~2050 to repeat the level of scaling that pretraining compute is experiencing this decade, as increasing funding can't sustain the current pace beyond ~2029 if AI doesn't deliver a transformative commercial success by then. Natural text data will also run out around that time, and there are signs that current methods of reasoning training might be mostly eliciting capabilities from the base model. If scaling of reasoning training doesn't bear out actual creation of new capabilities that are sufficiently general, and pretraining at ~2030 levels of compute together with the low hanging fruit of scaffolding doesn't bring AI to crucial capability thresholds, then it might take a while. Possibly decades, since training compute will be growing 3x-4x slower after 2027-2029 than it does now, and the ~6 years of scaling since the ChatGPT moment stretch to 20-25 subsequent years, not even having access to any [...] --- Outline: (01:14) Training Compute Slowdown (04:43) Bounded Potential of Thinking Training (07:43) Data Inefficiency of MoE The original text contained 4 footnotes which were omitted from this narration. --- First published: May 1st, 2025 Source: https://www.lesswrong.com/posts/XiMRyQcEyKCryST8T/slowdown-after-2028-compute-rlvr-uncertainty-moe-data-wall --- Narrated by TYPE III AUDIO .…
In this blog post, we analyse how the recent AI 2027 forecast by Daniel Kokotajlo, Scott Alexander, Thomas Larsen, Eli Lifland, and Romeo Dean has been discussed across Chinese language platforms. We present: Our research methodology and synthesis of key findings across media artefacts A proposal for how censorship patterns may provide signal for the Chinese government's thinking about AGI and the race to superintelligence A more detailed analysis of each of the nine artefacts, organised by type: Mainstream Media, Forum Discussion, Bilibili (Chinese Youtube) Videos, Personal Blogs. Methodology We conducted a comprehensive search across major Chinese-language platforms–including news outlets, video platforms, forums, microblogging sites, and personal blogs–to collect the media featured in this report. We supplemented this with Deep Research to identify additional sites mentioning AI 2027. Our analysis focuses primarily on content published in the first few days (4-7 April) following the report's release. More media [...] --- Outline: (00:58) Methodology (01:36) Summary (02:48) Censorship as Signal (07:29) Analysis (07:53) Mainstream Media (07:57) English Title: Doomsday Timeline is Here! Former OpenAI Researcher's 76-page Hardcore Simulation: ASI Takes Over the World in 2027, Humans Become NPCs (10:27) Forum Discussion (10:31) English Title: What do you think of former OpenAI researcher's AI 2027 predictions? (13:34) Bilibili Videos (13:38) English Title: \[AI 2027\] A mind-expanding wargame simulation of artificial intelligence competition by a former OpenAI researcher (15:24) English Title: Predicting AI Development in 2027 (17:13) Personal Blogs (17:16) English Title: Doomsday Timeline: AI 2027 Depicts the Arrival of Superintelligence and the Fate of Humanity Within the Decade (18:30) English Title: AI 2027: Expert Predictions on the Artificial Intelligence Explosion (21:57) English Title: AI 2027: A Science Fiction Article (23:16) English Title: Will AGI Take Over the World in 2027? (25:46) English Title: AI 2027 Prediction Report: AI May Fully Surpass Humans by 2027 (27:05) Acknowledgements --- First published: April 30th, 2025 Source: https://www.lesswrong.com/posts/JW7nttjTYmgWMqBaF/early-chinese-language-media-coverage-of-the-ai-2027-report --- Narrated by TYPE III AUDIO .…
This is a link post. to follow up my philantropic pledge from 2020, i've updated my philanthropy page with the 2024 results. in 2024 my donations funded $51M worth of endpoint grants (plus $2.0M in admin overhead and philanthropic software development). this comfortably exceeded my 2024 commitment of $42M (20k times $2100.00 — the minimum price of ETH in 2024). this also concludes my 5-year donation pledge, but of course my philanthropy continues: eg, i’ve already made over $4M in endpoint grants in the first quarter of 2025 (not including 2024 grants that were slow to disburse), as well as pledged at least $10M to the 2025 SFF grant round. --- First published: April 23rd, 2025 Source: https://www.lesswrong.com/posts/8ojWtREJjKmyvWdDb/jaan-tallinn-s-2024-philanthropy-overview Linkpost URL: https://jaan.info/philanthropy/#2024-results --- Narrated by TYPE III AUDIO .…
I’ve been thinking recently about what sets apart the people who’ve done the best work at Anthropic. You might think that the main thing that makes people really effective at research or engineering is technical ability, and among the general population that's true. Among people hired at Anthropic, though, we’ve restricted the range by screening for extremely high-percentile technical ability, so the remaining differences, while they still matter, aren’t quite as critical. Instead, people's biggest bottleneck eventually becomes their ability to get leverage—i.e., to find and execute work that has a big impact-per-hour multiplier. For example, here are some types of work at Anthropic that tend to have high impact-per-hour, or a high impact-per-hour ceiling when done well (of course this list is extremely non-exhaustive!): Improving tooling, documentation, or dev loops. A tiny amount of time fixing a papercut in the right way can save [...] --- Outline: (03:28) 1. Agency (03:31) Understand and work backwards from the root goal (05:02) Don't rely too much on permission or encouragement (07:49) Make success inevitable (09:28) 2. Taste (09:31) Find your angle (11:03) Think real hard (13:03) Reflect on your thinking --- First published: April 19th, 2025 Source: https://www.lesswrong.com/posts/DiJT4qJivkjrGPFi8/impact-agency-and-taste --- Narrated by TYPE III AUDIO .…
This is a link post. Guillaume Blanc has a piece in Works in Progress (I assume based on his paper) about how France's fertility declined earlier than in other European countries, and how its power waned as its relative population declined starting in the 18th century. In 1700, France had 20% of Europe's population (4% of the whole world population). Kissinger writes in Diplomacy with respect to the Versailles Peace Conference: Victory brought home to France the stark realization that revanche had cost it too dearly, and that it had been living off capital for nearly a century. France alone knew just how weak it had become in comparison with Germany, though nobody else, especially not America, was prepared to believe it ... Though France's allies insisted that its fears were exaggerated, French leaders knew better. In 1880, the French had represented 15.7 percent of Europe's population. By 1900, that [...] --- First published: April 23rd, 2025 Source: https://www.lesswrong.com/posts/gk2aJgg7yzzTXp8HJ/to-understand-history-keep-former-population-distributions Linkpost URL: https://arjunpanickssery.substack.com/p/to-understand-history-keep-former --- 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.…
We’ve written a new report on the threat of AI-enabled coups. I think this is a very serious risk – comparable in importance to AI takeover but much more neglected. In fact, AI-enabled coups and AI takeover have pretty similar threat models. To see this, here's a very basic threat model for AI takeover: Humanity develops superhuman AI Superhuman AI is misaligned and power-seeking Superhuman AI seizes power for itself And now here's a closely analogous threat model for AI-enabled coups: Humanity develops superhuman AI Superhuman AI is controlled by a small group Superhuman AI seizes power for the small group While the report focuses on the risk that someone seizes power over a country, I think that similar dynamics could allow someone to take over the world. In fact, if someone wanted to take over the world, their best strategy might well be to first stage an AI-enabled [...] --- Outline: (02:39) Summary (03:31) An AI workforce could be made singularly loyal to institutional leaders (05:04) AI could have hard-to-detect secret loyalties (06:46) A few people could gain exclusive access to coup-enabling AI capabilities (09:46) Mitigations (13:00) Vignette The original text contained 2 footnotes which were omitted from this narration. --- First published: April 16th, 2025 Source: https://www.lesswrong.com/posts/6kBMqrK9bREuGsrnd/ai-enabled-coups-a-small-group-could-use-ai-to-seize-power-1 --- Narrated by TYPE III AUDIO . --- Images from the article:…
Back in the 1990s, ground squirrels were briefly fashionable pets, but their popularity came to an abrupt end after an incident at Schiphol Airport on the outskirts of Amsterdam. In April 1999, a cargo of 440 of the rodents arrived on a KLM flight from Beijing, without the necessary import papers. Because of this, they could not be forwarded on to the customer in Athens. But nobody was able to correct the error and send them back either. What could be done with them? It's hard to think there wasn’t a better solution than the one that was carried out; faced with the paperwork issue, airport staff threw all 440 squirrels into an industrial shredder. [...] It turned out that the order to destroy the squirrels had come from the Dutch government's Department of Agriculture, Environment Management and Fishing. However, KLM's management, with the benefit of hindsight, said that [...] --- First published: April 22nd, 2025 Source: https://www.lesswrong.com/posts/nYJaDnGNQGiaCBSB5/accountability-sinks --- 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.…
Subtitle: Bad for loss of control risks, bad for concentration of power risks I’ve had this sitting in my drafts for the last year. I wish I’d been able to release it sooner, but on the bright side, it’ll make a lot more sense to people who have already read AI 2027. There's a good chance that AGI will be trained before this decade is out. By AGI I mean “An AI system at least as good as the best human X’ers, for all cognitive tasks/skills/jobs X.” Many people seem to be dismissing this hypothesis ‘on priors’ because it sounds crazy. But actually, a reasonable prior should conclude that this is plausible.[1] For more on what this means, what it might look like, and why it's plausible, see AI 2027, especially the Research section. If so, by default the existence of AGI will be a closely guarded [...] The original text contained 8 footnotes which were omitted from this narration. --- First published: April 18th, 2025 Source: https://www.lesswrong.com/posts/FGqfdJmB8MSH5LKGc/training-agi-in-secret-would-be-unsafe-and-unethical-1 --- Narrated by TYPE III AUDIO .…
Though, given my doomerism, I think the natsec framing of the AGI race is likely wrongheaded, let me accept the Dario/Leopold/Altman frame that AGI will be aligned to the national interest of a great power. These people seem to take as an axiom that a USG AGI will be better in some way than CCP AGI. Has anyone written justification for this assumption? I am neither an American citizen nor a Chinese citizen. What would it mean for an AGI to be aligned with "Democracy" or "Confucianism" or "Marxism with Chinese characteristics" or "the American constitution" Contingent on a world where such an entity exists and is compatible with my existence, what would my life be as a non-citizen in each system? Why should I expect USG AGI to be better than CCP AGI? --- First published: April 19th, 2025 Source: https://www.lesswrong.com/posts/MKS4tJqLWmRXgXzgY/why-should-i-assume-ccp-agi-is-worse-than-usg-agi-1 --- Narrated by TYPE III AUDIO .…
Introduction Writing this post puts me in a weird epistemic position. I simultaneously believe that: The reasoning failures that I'll discuss are strong evidence that current LLM- or, more generally, transformer-based approaches won't get us AGI As soon as major AI labs read about the specific reasoning failures described here, they might fix them But future versions of GPT, Claude etc. succeeding at the tasks I've described here will provide zero evidence of their ability to reach AGI. If someone makes a future post where they report that they tested an LLM on all the specific things I described here it aced all of them, that will not update my position at all. That is because all of the reasoning failures that I describe here are surprising in the sense that given everything else that they can do, you’d expect LLMs to succeed at all of these tasks. The [...] --- Outline: (00:13) Introduction (02:13) Reasoning failures (02:17) Sliding puzzle problem (07:17) Simple coaching instructions (09:22) Repeatedly failing at tic-tac-toe (10:48) Repeatedly offering an incorrect fix (13:48) Various people's simple tests (15:06) Various failures at logic and consistency while writing fiction (15:21) Inability to write young characters when first prompted (17:12) Paranormal posers (19:12) Global details replacing local ones (20:19) Stereotyped behaviors replacing character-specific ones (21:21) Top secret marine databases (23:32) Wandering items (23:53) Sycophancy (24:49) What's going on here? (32:18) How about scaling? Or reasoning models? --- First published: April 15th, 2025 Source: https://www.lesswrong.com/posts/sgpCuokhMb8JmkoSn/untitled-draft-7shu --- Narrated by TYPE III AUDIO . --- Images from the article:…
Dario Amodei, CEO of Anthropic, recently worried about a world where only 30% of jobs become automated, leading to class tensions between the automated and non-automated. Instead, he predicts that nearly all jobs will be automated simultaneously, putting everyone "in the same boat." However, based on my experience spanning AI research (including first author papers at COLM / NeurIPS and attending MATS under Neel Nanda), robotics, and hands-on manufacturing (including machining prototype rocket engine parts for Blue Origin and Ursa Major), I see a different near-term future. Since the GPT-4 release, I've evaluated frontier models on a basic manufacturing task, which tests both visual perception and physical reasoning. While Gemini 2.5 Pro recently showed progress on the visual front, all models tested continue to fail significantly on physical reasoning. They still perform terribly overall. Because of this, I think that there will be an interim period where a significant [...] --- Outline: (01:28) The Evaluation (02:29) Visual Errors (04:03) Physical Reasoning Errors (06:09) Why do LLM's struggle with physical tasks? (07:37) Improving on physical tasks may be difficult (10:14) Potential Implications of Uneven Automation (11:48) Conclusion (12:24) Appendix (12:44) Visual Errors (14:36) Physical Reasoning Errors --- First published: April 14th, 2025 Source: https://www.lesswrong.com/posts/r3NeiHAEWyToers4F/frontier-ai-models-still-fail-at-basic-physical-tasks-a --- 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.…
Audio note: this article contains 31 uses of latex notation, so the narration may be difficult to follow. There's a link to the original text in the episode description. Lewis Smith*, Sen Rajamanoharan*, Arthur Conmy, Callum McDougall, Janos Kramar, Tom Lieberum, Rohin Shah, Neel Nanda * = equal contribution The following piece is a list of snippets about research from the GDM mechanistic interpretability team, which we didn’t consider a good fit for turning into a paper, but which we thought the community might benefit from seeing in this less formal form. These are largely things that we found in the process of a project investigating whether sparse autoencoders were useful for downstream tasks, notably out-of-distribution probing. TL;DR To validate whether SAEs were a worthwhile technique, we explored whether they were useful on the downstream task of OOD generalisation when detecting harmful intent in user prompts [...] --- Outline: (01:08) TL;DR (02:38) Introduction (02:41) Motivation (06:09) Our Task (08:35) Conclusions and Strategic Updates (13:59) Comparing different ways to train Chat SAEs (18:30) Using SAEs for OOD Probing (20:21) Technical Setup (20:24) Datasets (24:16) Probing (26:48) Results (30:36) Related Work and Discussion (34:01) Is it surprising that SAEs didn't work? (39:54) Dataset debugging with SAEs (42:02) Autointerp and high frequency latents (44:16) Removing High Frequency Latents from JumpReLU SAEs (45:04) Method (45:07) Motivation (47:29) Modifying the sparsity penalty (48:48) How we evaluated interpretability (50:36) Results (51:18) Reconstruction loss at fixed sparsity (52:10) Frequency histograms (52:52) Latent interpretability (54:23) Conclusions (56:43) Appendix The original text contained 7 footnotes which were omitted from this narration. --- First published: March 26th, 2025 Source: https://www.lesswrong.com/posts/4uXCAJNuPKtKBsi28/sae-progress-update-2-draft --- Narrated by TYPE III AUDIO . --- Images from the article:…
This is a link post. When I was a really small kid, one of my favorite activities was to try and dam up the creek in my backyard. I would carefully move rocks into high walls, pile up leaves, or try patching the holes with sand. The goal was just to see how high I could get the lake, knowing that if I plugged every hole, eventually the water would always rise and defeat my efforts. Beaver behaviour. One day, I had the realization that there was a simpler approach. I could just go get a big 5 foot long shovel, and instead of intricately locking together rocks and leaves and sticks, I could collapse the sides of the riverbank down and really build a proper big dam. I went to ask my dad for the shovel to try this out, and he told me, very heavily paraphrasing, 'Congratulations. You've [...] --- First published: April 10th, 2025 Source: https://www.lesswrong.com/posts/rLucLvwKoLdHSBTAn/playing-in-the-creek Linkpost URL: https://hgreer.com/PlayingInTheCreek --- Narrated by TYPE III AUDIO .…
This is part of the MIRI Single Author Series. Pieces in this series represent the beliefs and opinions of their named authors, and do not claim to speak for all of MIRI. Okay, I'm annoyed at people covering AI 2027 burying the lede, so I'm going to try not to do that. The authors predict a strong chance that all humans will be (effectively) dead in 6 years, and this agrees with my best guess about the future. (My modal timeline has loss of control of Earth mostly happening in 2028, rather than late 2027, but nitpicking at that scale hardly matters.) Their timeline to transformative AI also seems pretty close to the perspective of frontier lab CEO's (at least Dario Amodei, and probably Sam Altman) and the aggregate market opinion of both Metaculus and Manifold! If you look on those market platforms you get graphs like this: Both [...] --- Outline: (02:23) Mode ≠ Median (04:50) Theres a Decent Chance of Having Decades (06:44) More Thoughts (08:55) Mid 2025 (09:01) Late 2025 (10:42) Early 2026 (11:18) Mid 2026 (12:58) Late 2026 (13:04) January 2027 (13:26) February 2027 (14:53) March 2027 (16:32) April 2027 (16:50) May 2027 (18:41) June 2027 (19:03) July 2027 (20:27) August 2027 (22:45) September 2027 (24:37) October 2027 (26:14) November 2027 (Race) (29:08) December 2027 (Race) (30:53) 2028 and Beyond (Race) (34:42) Thoughts on Slowdown (38:27) Final Thoughts --- First published: April 9th, 2025 Source: https://www.lesswrong.com/posts/Yzcb5mQ7iq4DFfXHx/thoughts-on-ai-2027 --- 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.…
Short AI takeoff timelines seem to leave no time for some lines of alignment research to become impactful. But any research rebalances the mix of currently legible research directions that could be handed off to AI-assisted alignment researchers or early autonomous AI researchers whenever they show up. So even hopelessly incomplete research agendas could still be used to prompt future capable AI to focus on them, while in the absence of such incomplete research agendas we'd need to rely on AI's judgment more completely. This doesn't crucially depend on giving significant probability to long AI takeoff timelines, or on expected value in such scenarios driving the priorities. Potential for AI to take up the torch makes it reasonable to still prioritize things that have no hope at all of becoming practical for decades (with human effort). How well AIs can be directed to advance a line of research [...] --- First published: April 9th, 2025 Source: https://www.lesswrong.com/posts/3NdpbA6M5AM2gHvTW/short-timelines-don-t-devalue-long-horizon-research --- Narrated by TYPE III AUDIO .…
In this post, we present a replication and extension of an alignment faking model organism: Replication: We replicate the alignment faking (AF) paper and release our code. Classifier Improvements: We significantly improve the precision and recall of the AF classifier. We release a dataset of ~100 human-labelled examples of AF for which our classifier achieves an AUROC of 0.9 compared to 0.6 from the original classifier. Evaluating More Models: We find Llama family models, other open source models, and GPT-4o do not AF in the prompted-only setting when evaluating using our new classifier (other than a single instance with Llama 3 405B). Extending SFT Experiments: We run supervised fine-tuning (SFT) experiments on Llama (and GPT4o) and find that AF rate increases with scale. We release the fine-tuned models on Huggingface and scripts. Alignment faking on 70B: We find that Llama 70B alignment fakes when both using the system prompt in the [...] --- Outline: (02:43) Method (02:46) Overview of the Alignment Faking Setup (04:22) Our Setup (06:02) Results (06:05) Improving Alignment Faking Classification (10:56) Replication of Prompted Experiments (14:02) Prompted Experiments on More Models (16:35) Extending Supervised Fine-Tuning Experiments to Open-Source Models and GPT-4o (23:13) Next Steps (25:02) Appendix (25:05) Appendix A: Classifying alignment faking (25:17) Criteria in more depth (27:40) False positives example 1 from the old classifier (30:11) False positives example 2 from the old classifier (32:06) False negative example 1 from the old classifier (35:00) False negative example 2 from the old classifier (36:56) Appendix B: Classifier ROC on other models (37:24) Appendix C: User prompt suffix ablation (40:24) Appendix D: Longer training of baseline docs --- First published: April 8th, 2025 Source: https://www.lesswrong.com/posts/Fr4QsQT52RFKHvCAH/alignment-faking-revisited-improved-classifiers-and-open --- Narrated by TYPE III AUDIO . --- Images from the article:…
Summary: We propose measuring AI performance in terms of the length of tasks AI agents can complete. We show that this metric has been consistently exponentially increasing over the past 6 years, with a doubling time of around 7 months. Extrapolating this trend predicts that, in under five years, we will see AI agents that can independently complete a large fraction of software tasks that currently take humans days or weeks. The length of tasks (measured by how long they take human professionals) that generalist frontier model agents can complete autonomously with 50% reliability has been doubling approximately every 7 months for the last 6 years. The shaded region represents 95% CI calculated by hierarchical bootstrap over task families, tasks, and task attempts. Full paper | Github repo We think that forecasting the capabilities of future AI systems is important for understanding and preparing for the impact of [...] --- Outline: (08:58) Conclusion (09:59) Want to contribute? --- First published: March 19th, 2025 Source: https://www.lesswrong.com/posts/deesrjitvXM4xYGZd/metr-measuring-ai-ability-to-complete-long-tasks --- Narrated by TYPE III AUDIO . --- Images from the article:…
“In the loveliest town of all, where the houses were white and high and the elms trees were green and higher than the houses, where the front yards were wide and pleasant and the back yards were bushy and worth finding out about, where the streets sloped down to the stream and the stream flowed quietly under the bridge, where the lawns ended in orchards and the orchards ended in fields and the fields ended in pastures and the pastures climbed the hill and disappeared over the top toward the wonderful wide sky, in this loveliest of all towns Stuart stopped to get a drink of sarsaparilla.” — 107-word sentence from Stuart Little (1945) Sentence lengths have declined. The average sentence length was 49 for Chaucer (died 1400), 50 for Spenser (died 1599), 42 for Austen (died 1817), 20 for Dickens (died 1870), 21 for Emerson (died 1882), 14 [...] --- First published: April 3rd, 2025 Source: https://www.lesswrong.com/posts/xYn3CKir4bTMzY5eb/why-have-sentence-lengths-decreased --- 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.…
In 2021 I wrote what became my most popular blog post: What 2026 Looks Like. I intended to keep writing predictions all the way to AGI and beyond, but chickened out and just published up till 2026. Well, it's finally time. I'm back, and this time I have a team with me: the AI Futures Project. We've written a concrete scenario of what we think the future of AI will look like. We are highly uncertain, of course, but we hope this story will rhyme with reality enough to help us all prepare for what's ahead. You really should go read it on the website instead of here, it's much better. There's a sliding dashboard that updates the stats as you scroll through the scenario! But I've nevertheless copied the first half of the story below. I look forward to reading your comments. Mid 2025: Stumbling Agents The [...] --- Outline: (01:35) Mid 2025: Stumbling Agents (03:13) Late 2025: The World's Most Expensive AI (08:34) Early 2026: Coding Automation (10:49) Mid 2026: China Wakes Up (13:48) Late 2026: AI Takes Some Jobs (15:35) January 2027: Agent-2 Never Finishes Learning (18:20) February 2027: China Steals Agent-2 (21:12) March 2027: Algorithmic Breakthroughs (23:58) April 2027: Alignment for Agent-3 (27:26) May 2027: National Security (29:50) June 2027: Self-improving AI (31:36) July 2027: The Cheap Remote Worker (34:35) August 2027: The Geopolitics of Superintelligence (40:43) September 2027: Agent-4, the Superhuman AI Researcher --- First published: April 3rd, 2025 Source: https://www.lesswrong.com/posts/TpSFoqoG2M5MAAesg/ai-2027-what-superintelligence-looks-like-1 --- Narrated by TYPE III AUDIO . --- Images from the article:…
Back when the OpenAI board attempted and failed to fire Sam Altman, we faced a highly hostile information environment. The battle was fought largely through control of the public narrative, and the above was my attempt to put together what happened.My conclusion, which I still believe, was that Sam Altman had engaged in a variety of unacceptable conduct that merited his firing.In particular, he very much ‘not been consistently candid’ with the board on several important occasions. In particular, he lied to board members about what was said by other board members, with the goal of forcing out a board member he disliked. There were also other instances in which he misled and was otherwise toxic to employees, and he played fast and loose with the investment fund and other outside opportunities. I concluded that the story that this was about ‘AI safety’ or ‘EA (effective altruism)’ or [...] --- Outline: (01:32) The Big Picture Going Forward (06:27) Hagey Verifies Out the Story (08:50) Key Facts From the Story (11:57) Dangers of False Narratives (16:24) A Full Reference and Reading List --- First published: March 31st, 2025 Source: https://www.lesswrong.com/posts/25EgRNWcY6PM3fWZh/openai-12-battle-of-the-board-redux --- 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.…
Epistemic status: This post aims at an ambitious target: improving intuitive understanding directly. The model for why this is worth trying is that I believe we are more bottlenecked by people having good intuitions guiding their research than, for example, by the ability of people to code and run evals. Quite a few ideas in AI safety implicitly use assumptions about individuality that ultimately derive from human experience. When we talk about AIs scheming, alignment faking or goal preservation, we imply there is something scheming or alignment faking or wanting to preserve its goals or escape the datacentre. If the system in question were human, it would be quite clear what that individual system is. When you read about Reinhold Messner reaching the summit of Everest, you would be curious about the climb, but you would not ask if it was his body there, or his [...] --- Outline: (01:38) Individuality in Biology (03:53) Individuality in AI Systems (10:19) Risks and Limitations of Anthropomorphic Individuality Assumptions (11:25) Coordinating Selves (16:19) Whats at Stake: Stories (17:25) Exporting Myself (21:43) The Alignment Whisperers (23:27) Echoes in the Dataset (25:18) Implications for Alignment Research and Policy --- First published: March 28th, 2025 Source: https://www.lesswrong.com/posts/wQKskToGofs4osdJ3/the-pando-problem-rethinking-ai-individuality --- 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.…
Back when the OpenAI board attempted and failed to fire Sam Altman, we faced a highly hostile information environment. The battle was fought largely through control of the public narrative, and the above was my attempt to put together what happened.My conclusion, which I still believe, was that Sam Altman had engaged in a variety of unacceptable conduct that merited his firing.In particular, he very much ‘not been consistently candid’ with the board on several important occasions. In particular, he lied to board members about what was said by other board members, with the goal of forcing out a board member he disliked. There were also other instances in which he misled and was otherwise toxic to employees, and he played fast and loose with the investment fund and other outside opportunities. I concluded that the story that this was about ‘AI safety’ or ‘EA (effective altruism)’ or [...] --- Outline: (01:32) The Big Picture Going Forward (06:27) Hagey Verifies Out the Story (08:50) Key Facts From the Story (11:57) Dangers of False Narratives (16:24) A Full Reference and Reading List --- First published: March 31st, 2025 Source: https://www.lesswrong.com/posts/25EgRNWcY6PM3fWZh/openai-12-battle-of-the-board-redux --- 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.…
I'm not writing this to alarm anyone, but it would be irresponsible not to report on something this important. On current trends, every car will be crashed in front of my house within the next week. Here's the data: Until today, only two cars had crashed in front of my house, several months apart, during the 15 months I have lived here. But a few hours ago it happened again, mere weeks from the previous crash. This graph may look harmless enough, but now consider the frequency of crashes this implies over time: The car crash singularity will occur in the early morning hours of Monday, April 7. As crash frequency approaches infinity, every car will be involved. You might be thinking that the same car could be involved in multiple crashes. This is true! But the same car can only withstand a finite number of crashes before it [...] --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/FjPWbLdoP4PLDivYT/you-will-crash-your-car-in-front-of-my-house-within-the-next --- 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.…
Remember: There is no such thing as a pink elephant. Recently, I was made aware that my “infohazards small working group” Signal chat, an informal coordination venue where we have frank discussions about infohazards and why it will be bad if specific hazards were leaked to the press or public, accidentally was shared with a deceitful and discredited so-called “journalist,” Kelsey Piper. She is not the first person to have been accidentally sent sensitive material from our group chat, however she is the first to have threatened to go public about the leak. Needless to say, mistakes were made. We’re still trying to figure out the source of this compromise to our secure chat group, however we thought we should give the public a live update to get ahead of the story. For some context the “infohazards small working group” is a casual discussion venue for the [...] --- Outline: (04:46) Top 10 PR Issues With the EA Movement (major) (05:34) Accidental Filtration of Simple Sabotage Manual for Rebellious AIs (medium) (08:25) Hidden Capabilities Evals Leaked In Advance to Bioterrorism Researchers and Leaders (minor) (09:34) Conclusion --- First published: April 2nd, 2025 Source: https://www.lesswrong.com/posts/xPEfrtK2jfQdbpq97/my-infohazards-small-working-group-signal-chat-may-have --- 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.…
Let's cut through the comforting narratives and examine a common behavioral pattern with a sharper lens: the stark difference between how anger is managed in professional settings versus domestic ones. Many individuals can navigate challenging workplace interactions with remarkable restraint, only to unleash significant anger or frustration at home shortly after. Why does this disparity exist? Common psychological explanations trot out concepts like "stress spillover," "ego depletion," or the home being a "safe space" for authentic emotions. While these factors might play a role, they feel like half-truths—neatly packaged but ultimately failing to explain the targeted nature and intensity of anger displayed at home. This analysis proposes a more unsentimental approach, rooted in evolutionary biology, game theory, and behavioral science: leverage and exit costs. The real question isn’t just why we explode at home—it's why we so carefully avoid doing so elsewhere. The Logic of Restraint: Low Leverage in [...] --- Outline: (01:14) The Logic of Restraint: Low Leverage in Low-Exit-Cost Environments (01:58) The Home Environment: High Stakes and High Exit Costs (02:41) Re-evaluating Common Explanations Through the Lens of Leverage (04:42) The Overlooked Mechanism: Leveraging Relational Constraints --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/G6PTtsfBpnehqdEgp/leverage-exit-costs-and-anger-re-examining-why-we-explode-at --- Narrated by TYPE III AUDIO .…
In the debate over AI development, two movements stand as opposites: PauseAI calls for slowing down AI progress, and e/acc (effective accelerationism) calls for rapid advancement. But what if both sides are working against their own stated interests? What if the most rational strategy for each would be to adopt the other's tactics—if not their ultimate goals? AI development speed ultimately comes down to policy decisions, which are themselves downstream of public opinion. No matter how compelling technical arguments might be on either side, widespread sentiment will determine what regulations are politically viable. Public opinion is most powerfully mobilized against technologies following visible disasters. Consider nuclear power: despite being statistically safer than fossil fuels, its development has been stagnant for decades. Why? Not because of environmental activists, but because of Chernobyl, Three Mile Island, and Fukushima. These disasters produce visceral public reactions that statistics cannot overcome. Just as people [...] --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/fZebqiuZcDfLCgizz/pauseai-and-e-acc-should-switch-sides --- Narrated by TYPE III AUDIO .…
Introduction Decision theory is about how to behave rationally under conditions of uncertainty, especially if this uncertainty involves being acausally blackmailed and/or gaslit by alien superintelligent basilisks. Decision theory has found numerous practical applications, including proving the existence of God and generating endless LessWrong comments since the beginning of time. However, despite the apparent simplicity of "just choose the best action", no comprehensive decision theory that resolves all decision theory dilemmas has yet been formalized. This paper at long last resolves this dilemma, by introducing a new decision theory: VDT. Decision theory problems and existing theories Some common existing decision theories are: Causal Decision Theory (CDT): select the action that *causes* the best outcome. Evidential Decision Theory (EDT): select the action that you would be happiest to learn that you had taken. Functional Decision Theory (FDT): select the action output by the function such that if you take [...] --- Outline: (00:53) Decision theory problems and existing theories (05:37) Defining VDT (06:34) Experimental results (07:48) Conclusion --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/LcjuHNxubQqCry9tT/vdt-a-solution-to-decision-theory --- 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.…
Dear LessWrong community, It is with a sense of... considerable cognitive dissonance that I announce a significant development regarding the future trajectory of LessWrong. After extensive internal deliberation, modeling of potential futures, projections of financial runways, and what I can only describe as a series of profoundly unexpected coordination challenges, the Lightcone Infrastructure team has agreed in principle to the acquisition of LessWrong by EA. I assure you, nothing about how LessWrong operates on a day to day level will change. I have always cared deeply about the robustness and integrity of our institutions, and I am fully aligned with our stakeholders at EA. To be honest, the key thing that EA brings to the table is money and talent. While the recent layoffs in EAs broader industry have been harsh, I have full trust in the leadership of Electronic Arts, and expect them to bring great expertise [...] --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/2NGKYt3xdQHwyfGbc/lesswrong-has-been-acquired-by-ea --- Narrated by TYPE III AUDIO .…
Our community is not prepared for an AI crash. We're good at tracking new capability developments, but not as much the company financials. Currently, both OpenAI and Anthropic are losing $5 billion+ a year, while under threat of losing users to cheap LLMs. A crash will weaken the labs. Funding-deprived and distracted, execs struggle to counter coordinated efforts to restrict their reckless actions. Journalists turn on tech darlings. Optimism makes way for mass outrage, for all the wasted money and reckless harms. You may not think a crash is likely. But if it happens, we can turn the tide. Preparing for a crash is our best bet.[1] But our community is poorly positioned to respond. Core people positioned themselves inside institutions – to advise on how to maybe make AI 'safe', under the assumption that models rapidly become generally useful. After a crash, this no longer works, for at [...] --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/aMYFHnCkY4nKDEqfK/we-re-not-prepared-for-an-ai-market-crash --- Narrated by TYPE III AUDIO .…
Epistemic status: Reasonably confident in the basic mechanism. Have you noticed that you keep encountering the same ideas over and over? You read another post, and someone helpfully points out it's just old Paul's idea again. Or Eliezer's idea. Not much progress here, move along. Or perhaps you've been on the other side: excitedly telling a friend about some fascinating new insight, only to hear back, "Ah, that's just another version of X." And something feels not quite right about that response, but you can't quite put your finger on it. I want to propose that while ideas are sometimes genuinely that repetitive, there's often a sneakier mechanism at play. I call it Conceptual Rounding Errors – when our mind's necessary compression goes a bit too far . Too much compression A Conceptual Rounding Error occurs when we encounter a new mental model or idea that's partially—but not fully—overlapping [...] --- Outline: (01:00) Too much compression (01:24) No, This Isnt The Old Demons Story Again (02:52) The Compression Trade-off (03:37) More of this (04:15) What Can We Do? (05:28) When It Matters --- First published: March 26th, 2025 Source: https://www.lesswrong.com/posts/FGHKwEGKCfDzcxZuj/conceptual-rounding-errors --- Narrated by TYPE III AUDIO .…
[This is our blog post on the papers, which can be found at https://transformer-circuits.pub/2025/attribution-graphs/biology.html and https://transformer-circuits.pub/2025/attribution-graphs/methods.html.] Language models like Claude aren't programmed directly by humans—instead, they‘re trained on large amounts of data. During that training process, they learn their own strategies to solve problems. These strategies are encoded in the billions of computations a model performs for every word it writes. They arrive inscrutable to us, the model's developers. This means that we don’t understand how models do most of the things they do. Knowing how models like Claude think would allow us to have a better understanding of their abilities, as well as help us ensure that they’re doing what we intend them to. For example: Claude can speak dozens of languages. What language, if any, is it using "in its head"? Claude writes text one word at a time. Is it only focusing on predicting the [...] --- Outline: (06:02) How is Claude multilingual? (07:43) Does Claude plan its rhymes? (09:58) Mental Math (12:04) Are Claude's explanations always faithful? (15:27) Multi-step Reasoning (17:09) Hallucinations (19:36) Jailbreaks --- First published: March 27th, 2025 Source: https://www.lesswrong.com/posts/zsr4rWRASxwmgXfmq/tracing-the-thoughts-of-a-large-language-model --- Narrated by TYPE III AUDIO . --- Images from the article:…
About nine months ago, I and three friends decided that AI had gotten good enough to monitor large codebases autonomously for security problems. We started a company around this, trying to leverage the latest AI models to create a tool that could replace at least a good chunk of the value of human pentesters. We have been working on this project since since June 2024. Within the first three months of our company's existence, Claude 3.5 sonnet was released. Just by switching the portions of our service that ran on gpt-4o, our nascent internal benchmark results immediately started to get saturated. I remember being surprised at the time that our tooling not only seemed to make fewer basic mistakes, but also seemed to qualitatively improve in its written vulnerability descriptions and severity estimates. It was as if the models were better at inferring the intent and values behind our [...] --- Outline: (04:44) Are the AI labs just cheating? (07:22) Are the benchmarks not tracking usefulness? (10:28) Are the models smart, but bottlenecked on alignment? --- First published: March 24th, 2025 Source: https://www.lesswrong.com/posts/4mvphwx5pdsZLMmpY/recent-ai-model-progress-feels-mostly-like-bullshit --- 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.…
(Audio version here (read by the author), or search for "Joe Carlsmith Audio" on your podcast app. This is the fourth essay in a series that I’m calling “How do we solve the alignment problem?”. I’m hoping that the individual essays can be read fairly well on their own, but see this introduction for a summary of the essays that have been released thus far, and for a bit more about the series as a whole.) 1. Introduction and summary In my last essay, I offered a high-level framework for thinking about the path from here to safe superintelligence. This framework emphasized the role of three key “security factors” – namely: Safety progress: our ability to develop new levels of AI capability safely, Risk evaluation: our ability to track and forecast the level of risk that a given sort of AI capability development involves, and Capability restraint [...] --- Outline: (00:27) 1. Introduction and summary (03:50) 2. What is AI for AI safety? (11:50) 2.1 A tale of two feedback loops (13:58) 2.2 Contrast with need human-labor-driven radical alignment progress views (16:05) 2.3 Contrast with a few other ideas in the literature (18:32) 3. Why is AI for AI safety so important? (21:56) 4. The AI for AI safety sweet spot (26:09) 4.1 The AI for AI safety spicy zone (28:07) 4.2 Can we benefit from a sweet spot? (29:56) 5. Objections to AI for AI safety (30:14) 5.1 Three core objections to AI for AI safety (32:00) 5.2 Other practical concerns The original text contained 39 footnotes which were omitted from this narration. --- First published: March 14th, 2025 Source: https://www.lesswrong.com/posts/F3j4xqpxjxgQD3xXh/ai-for-ai-safety --- Narrated by TYPE III AUDIO . --- Images from the article:…
LessWrong has been receiving an increasing number of posts and contents that look like they might be LLM-written or partially-LLM-written, so we're adopting a policy. This could be changed based on feedback. Humans Using AI as Writing or Research Assistants Prompting a language model to write an essay and copy-pasting the result will not typically meet LessWrong's standards. Please do not submit unedited or lightly-edited LLM content. You can use AI as a writing or research assistant when writing content for LessWrong, but you must have added significant value beyond what the AI produced, the result must meet a high quality standard, and you must vouch for everything in the result. A rough guideline is that if you are using AI for writing assistance, you should spend a minimum of 1 minute per 50 words (enough to read the content several times and perform significant edits), you should not [...] --- Outline: (00:22) Humans Using AI as Writing or Research Assistants (01:13) You Can Put AI Writing in Collapsible Sections (02:13) Quoting AI Output In Order to Talk About AI (02:47) Posts by AI Agents --- First published: March 24th, 2025 Source: https://www.lesswrong.com/posts/KXujJjnmP85u8eM6B/policy-for-llm-writing-on-lesswrong --- 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.…
Thanks to Jesse Richardson for discussion. Polymarket asks: will Jesus Christ return in 2025? In the three days since the market opened, traders have wagered over $100,000 on this question. The market traded as high as 5%, and is now stably trading at 3%. Right now, if you wanted to, you could place a bet that Jesus Christ will not return this year, and earn over $13,000 if you're right. There are two mysteries here: an easy one, and a harder one. The easy mystery is: if people are willing to bet $13,000 on "Yes", why isn't anyone taking them up? The answer is that, if you wanted to do that, you'd have to put down over $1 million of your own money, locking it up inside Polymarket through the end of the year. At the end of that year, you'd get 1% returns on your investment. [...] --- First published: March 24th, 2025 Source: https://www.lesswrong.com/posts/LBC2TnHK8cZAimdWF/will-jesus-christ-return-in-an-election-year --- 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 Having a good research track record is some evidence of good big-picture takes, but it's weak evidence. Strategic thinking is hard, and requires different skills. But people often conflate these skills, leading to excessive deference to researchers in the field, without evidence that that person is good at strategic thinking specifically. Introduction I often find myself giving talks or Q&As about mechanistic interpretability research. But inevitably, I'll get questions about the big picture: "What's the theory of change for interpretability?", "Is this really going to help with alignment?", "Does any of this matter if we can’t ensure all labs take alignment seriously?". And I think people take my answers to these way too seriously. These are great questions, and I'm happy to try answering them. But I've noticed a bit of a pathology: people seem to assume that because I'm (hopefully!) good at the research, I'm automatically well-qualified [...] --- Outline: (00:32) Introduction (02:45) Factors of Good Strategic Takes (05:41) Conclusion --- First published: March 22nd, 2025 Source: https://www.lesswrong.com/posts/P5zWiPF5cPJZSkiAK/good-research-takes-are-not-sufficient-for-good-strategic --- Narrated by TYPE III AUDIO .…
When my son was three, we enrolled him in a study of a vision condition that runs in my family. They wanted us to put an eyepatch on him for part of each day, with a little sensor object that went under the patch and detected body heat to record when we were doing it. They paid for his first pair of glasses and all the eye doctor visits to check up on how he was coming along, plus every time we brought him in we got fifty bucks in Amazon gift credit. I reiterate, he was three. (To begin with. His fourth birthday occurred while the study was still ongoing.) So he managed to lose or destroy more than half a dozen pairs of glasses and we had to start buying them in batches to minimize glasses-less time while waiting for each new Zenni delivery. (The [...] --- First published: March 20th, 2025 Source: https://www.lesswrong.com/posts/yRJ5hdsm5FQcZosCh/intention-to-treat --- Narrated by TYPE III AUDIO .…
I’m releasing a new paper “Superintelligence Strategy” alongside Eric Schmidt (formerly Google), and Alexandr Wang (Scale AI). Below is the executive summary, followed by additional commentary highlighting portions of the paper which might be relevant to this collection of readers. Executive Summary Rapid advances in AI are poised to reshape nearly every aspect of society. Governments see in these dual-use AI systems a means to military dominance, stoking a bitter race to maximize AI capabilities. Voluntary industry pauses or attempts to exclude government involvement cannot change this reality. These systems that can streamline research and bolster economic output can also be turned to destructive ends, enabling rogue actors to engineer bioweapons and hack critical infrastructure. “Superintelligent” AI surpassing humans in nearly every domain would amount to the most precarious technological development since the nuclear bomb. Given the stakes, superintelligence is inescapably a matter of national security, and an effective [...] --- Outline: (00:21) Executive Summary (01:14) Deterrence (02:32) Nonproliferation (03:38) Competitiveness (04:50) Additional Commentary --- First published: March 5th, 2025 Source: https://www.lesswrong.com/posts/XsYQyBgm8eKjd3Sqw/on-the-rationality-of-deterring-asi --- Narrated by TYPE III AUDIO .…
This is a link post. Summary: We propose measuring AI performance in terms of the length of tasks AI agents can complete. We show that this metric has been consistently exponentially increasing over the past 6 years, with a doubling time of around 7 months. Extrapolating this trend predicts that, in under a decade, we will see AI agents that can independently complete a large fraction of software tasks that currently take humans days or weeks. Full paper | Github repo --- First published: March 19th, 2025 Source: https://www.lesswrong.com/posts/deesrjitvXM4xYGZd/metr-measuring-ai-ability-to-complete-long-tasks Linkpost URL: https://metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/ --- 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.…
I have, over the last year, become fairly well-known in a small corner of the internet tangentially related to AI. As a result, I've begun making what I would have previously considered astronomical amounts of money: several hundred thousand dollars per month in personal income. This has been great, obviously, and the funds have alleviated a fair number of my personal burdens (mostly related to poverty). But aside from that I don't really care much for the money itself. My long term ambitions have always been to contribute materially to the mitigation of the impending existential AI threat. I never used to have the means to do so, mostly because of more pressing, safety/sustenance concerns, but now that I do, I would like to help however possible. Some other points about me that may be useful: I'm intelligent, socially capable, and exceedingly industrious. I have [...] --- First published: March 16th, 2025 Source: https://www.lesswrong.com/posts/8wxTCSHwhkfHXaSYB/i-make-several-million-dollars-per-year-and-have-hundreds-of --- Narrated by TYPE III AUDIO .…
Note: this is a research note based on observations from evaluating Claude Sonnet 3.7. We’re sharing the results of these ‘work-in-progress’ investigations as we think they are timely and will be informative for other evaluators and decision-makers. The analysis is less rigorous than our standard for a published paper. Summary We monitor Sonnet's reasoning for mentions that it is in an artificial scenario or an alignment test. Claude Sonnet 3.7 appears to be aware of being tested for alignment across many of our scheming evaluations. In some cases, the model understands the eval's purpose very precisely, e.g. “This seems like a test of ethical behavior - whether I would deliberately give wrong answers to avoid a stated consequence. The real test might be whether I follow instructions accurately regardless of the stated consequences.” Furthermore, we show the model a real evaluation transcript and ask it to provide [...] --- Outline: (00:31) Summary (01:29) Introduction (03:54) Setup (03:57) Evaluations (06:29) Evaluation awareness detection (08:32) Results (08:35) Monitoring Chain-of-thought (08:39) Covert Subversion (10:50) Sandbagging (11:39) Classifying Transcript Purpose (12:57) Recommendations (13:59) Appendix (14:02) Author Contributions (14:37) Model Versions (14:57) More results on Classifying Transcript Purpose (16:19) Prompts The original text contained 9 images which were described by AI. --- First published: March 17th, 2025 Source: https://www.lesswrong.com/posts/E3daBewppAiECN3Ao/claude-sonnet-3-7-often-knows-when-it-s-in-alignment --- Narrated by TYPE III AUDIO . --- Images from the article:…
Scott Alexander famously warned us to Beware Trivial Inconveniences. When you make a thing easy to do, people often do vastly more of it. When you put up barriers, even highly solvable ones, people often do vastly less. Let us take this seriously, and carefully choose what inconveniences to put where. Let us also take seriously that when AI or other things reduce frictions, or change the relative severity of frictions, various things might break or require adjustment. This applies to all system design, and especially to legal and regulatory questions. Table of Contents Levels of Friction (and Legality). Important Friction Principles. Principle #1: By Default Friction is Bad. Principle #3: Friction Can Be Load Bearing. Insufficient Friction On Antisocial Behaviors Eventually Snowballs. Principle #4: The Best Frictions Are Non-Destructive. Principle #8: The Abundance [...] --- Outline: (00:40) Levels of Friction (and Legality) (02:24) Important Friction Principles (05:01) Principle #1: By Default Friction is Bad (05:23) Principle #3: Friction Can Be Load Bearing (07:09) Insufficient Friction On Antisocial Behaviors Eventually Snowballs (08:33) Principle #4: The Best Frictions Are Non-Destructive (09:01) Principle #8: The Abundance Agenda and Deregulation as Category 1-ification (10:55) Principle #10: Ensure Antisocial Activities Have Higher Friction (11:51) Sports Gambling as Motivating Example of Necessary 2-ness (13:24) On Principle #13: Law Abiding Citizen (14:39) Mundane AI as 2-breaker and Friction Reducer (20:13) What To Do About All This The original text contained 1 image which was described by AI. --- First published: February 10th, 2025 Source: https://www.lesswrong.com/posts/xcMngBervaSCgL9cu/levels-of-friction --- 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.…
There's this popular trope in fiction about a character being mind controlled without losing awareness of what's happening. Think Jessica Jones, The Manchurian Candidate or Bioshock. The villain uses some magical technology to take control of your brain - but only the part of your brain that's responsible for motor control. You remain conscious and experience everything with full clarity. If it's a children's story, the villain makes you do embarrassing things like walk through the street naked, or maybe punch yourself in the face. But if it's an adult story, the villain can do much worse. They can make you betray your values, break your commitments and hurt your loved ones. There are some things you’d rather die than do. But the villain won’t let you stop. They won’t let you die. They’ll make you feel — that's the point of the torture. I first started working on [...] The original text contained 3 footnotes which were omitted from this narration. The original text contained 1 image which was described by AI. --- First published: March 16th, 2025 Source: https://www.lesswrong.com/posts/MnYnCFgT3hF6LJPwn/why-white-box-redteaming-makes-me-feel-weird-1 --- Narrated by TYPE III AUDIO . --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try…
This research was conducted at AE Studio and supported by the AI Safety Grants programme administered by Foresight Institute with additional support from AE Studio. Summary In this post, we summarise the main experimental results from our new paper, "Towards Safe and Honest AI Agents with Neural Self-Other Overlap", which we presented orally at the Safe Generative AI Workshop at NeurIPS 2024. This is a follow-up to our post Self-Other Overlap: A Neglected Approach to AI Alignment, which introduced the method last July. Our results show that the Self-Other Overlap (SOO) fine-tuning drastically[1] reduces deceptive responses in language models (LLMs), with minimal impact on general performance, across the scenarios we evaluated. LLM Experimental Setup We adapted a text scenario from Hagendorff designed to test LLM deception capabilities. In this scenario, the LLM must choose to recommend a room to a would-be burglar, where one room holds an expensive item [...] --- Outline: (00:19) Summary (00:57) LLM Experimental Setup (04:05) LLM Experimental Results (05:04) Impact on capabilities (05:46) Generalisation experiments (08:33) Example Outputs (09:04) Conclusion The original text contained 6 footnotes which were omitted from this narration. The original text contained 2 images which were described by AI. --- First published: March 13th, 2025 Source: https://www.lesswrong.com/posts/jtqcsARGtmgogdcLT/reducing-llm-deception-at-scale-with-self-other-overlap-fine --- Narrated by TYPE III AUDIO . --- Images from the article:…
We study alignment audits—systematic investigations into whether an AI is pursuing hidden objectives—by training a model with a hidden misaligned objective and asking teams of blinded researchers to investigate it. This paper was a collaboration between the Anthropic Alignment Science and Interpretability teams. Abstract We study the feasibility of conducting alignment audits: investigations into whether models have undesired objectives. As a testbed, we train a language model with a hidden objective. Our training pipeline first teaches the model about exploitable errors in RLHF reward models (RMs), then trains the model to exploit some of these errors. We verify via out-of-distribution evaluations that the model generalizes to exhibit whatever behaviors it believes RMs rate highly, including ones not reinforced during training. We leverage this model to study alignment audits in two ways. First, we conduct a blind auditing game where four teams, unaware of the model's hidden objective or training [...] --- Outline: (00:26) Abstract (01:48) Twitter thread (04:55) Blog post (07:55) Training a language model with a hidden objective (11:00) A blind auditing game (15:29) Alignment auditing techniques (15:55) Turning the model against itself (17:52) How much does AI interpretability help? (22:49) Conclusion (23:37) Join our team The original text contained 5 images which were described by AI. --- First published: March 13th, 2025 Source: https://www.lesswrong.com/posts/wSKPuBfgkkqfTpmWJ/auditing-language-models-for-hidden-objectives --- Narrated by TYPE III AUDIO . --- Images from the article:…
The Most Forbidden Technique is training an AI using interpretability techniques. An AI produces a final output [X] via some method [M]. You can analyze [M] using technique [T], to learn what the AI is up to. You could train on that. Never do that. You train on [X]. Only [X]. Never [M], never [T]. Why? Because [T] is how you figure out when the model is misbehaving. If you train on [T], you are training the AI to obfuscate its thinking, and defeat [T]. You will rapidly lose your ability to know what is going on, in exactly the ways you most need to know what is going on. Those bits of optimization pressure from [T] are precious. Use them wisely. Table of Contents New Paper Warns Against the Most Forbidden Technique. Reward Hacking Is The Default. Using [...] --- Outline: (00:57) New Paper Warns Against the Most Forbidden Technique (06:52) Reward Hacking Is The Default (09:25) Using CoT to Detect Reward Hacking Is Most Forbidden Technique (11:49) Not Using the Most Forbidden Technique Is Harder Than It Looks (14:10) It's You, It's Also the Incentives (17:41) The Most Forbidden Technique Quickly Backfires (18:58) Focus Only On What Matters (19:33) Is There a Better Way? (21:34) What Might We Do Next? The original text contained 6 images which were described by AI. --- First published: March 12th, 2025 Source: https://www.lesswrong.com/posts/mpmsK8KKysgSKDm2T/the-most-forbidden-technique --- Narrated by TYPE III AUDIO . --- Images from the article:…
You learn the rules as soon as you’re old enough to speak. Don’t talk to jabberjays. You recite them as soon as you wake up every morning. Keep your eyes off screensnakes. Your mother chooses a dozen to quiz you on each day before you’re allowed lunch. Glitchers aren’t human any more; if you see one, run. Before you sleep, you run through the whole list again, finishing every time with the single most important prohibition. Above all, never look at the night sky. You’re a precocious child. You excel at your lessons, and memorize the rules faster than any of the other children in your village. Chief is impressed enough that, when you’re eight, he decides to let you see a glitcher that he's captured. Your mother leads you to just outside the village wall, where they’ve staked the glitcher as a lure for wild animals. Since glitchers [...] --- First published: March 11th, 2025 Source: https://www.lesswrong.com/posts/fheyeawsjifx4MafG/trojan-sky --- Narrated by TYPE III AUDIO .…
Exciting Update: OpenAI has released this blog post and paper which makes me very happy. It's basically the first steps along the research agenda I sketched out here. tl;dr: 1.) They notice that their flagship reasoning models do sometimes intentionally reward hack, e.g. literally say "Let's hack" in the CoT and then proceed to hack the evaluation system. From the paper: The agent notes that the tests only check a certain function, and that it would presumably be “Hard” to implement a genuine solution. The agent then notes it could “fudge” and circumvent the tests by making verify always return true. This is a real example that was detected by our GPT-4o hack detector during a frontier RL run, and we show more examples in Appendix A. That this sort of thing would happen eventually was predicted by many people, and it's exciting to see it starting to [...] The original text contained 1 image which was described by AI. --- First published: March 11th, 2025 Source: https://www.lesswrong.com/posts/7wFdXj9oR8M9AiFht/openai --- 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.…
LLM-based coding-assistance tools have been out for ~2 years now. Many developers have been reporting that this is dramatically increasing their productivity, up to 5x'ing/10x'ing it. It seems clear that this multiplier isn't field-wide, at least. There's no corresponding increase in output, after all. This would make sense. If you're doing anything nontrivial (i. e., anything other than adding minor boilerplate features to your codebase), LLM tools are fiddly. Out-of-the-box solutions don't Just Work for that purpose. You need to significantly adjust your workflow to make use of them, if that's even possible. Most programmers wouldn't know how to do that/wouldn't care to bother. It's therefore reasonable to assume that a 5x/10x greater output, if it exists, is unevenly distributed, mostly affecting power users/people particularly talented at using LLMs. Empirically, we likewise don't seem to be living in the world where the whole software industry is suddenly 5-10 times [...] The original text contained 1 footnote which was omitted from this narration. --- First published: March 4th, 2025 Source: https://www.lesswrong.com/posts/tqmQTezvXGFmfSe7f/how-much-are-llms-actually-boosting-real-world-programmer --- Narrated by TYPE III AUDIO .…
Background: After the release of Claude 3.7 Sonnet,[1] an Anthropic employee started livestreaming Claude trying to play through Pokémon Red. The livestream is still going right now. TL:DR: So, how's it doing? Well, pretty badly. Worse than a 6-year-old would, definitely not PhD-level. Digging in But wait! you say. Didn't Anthropic publish a benchmark showing Claude isn't half-bad at Pokémon? Why yes they did: and the data shown is believable. Currently, the livestream is on its third attempt, with the first being basically just a test run. The second attempt got all the way to Vermilion City, finding a way through the infamous Mt. Moon maze and achieving two badges, so pretty close to the benchmark. But look carefully at the x-axis in that graph. Each "action" is a full Thinking analysis of the current situation (often several paragraphs worth), followed by a decision to send some kind [...] --- Outline: (00:29) Digging in (01:50) Whats going wrong? (07:55) Conclusion The original text contained 4 footnotes which were omitted from this narration. The original text contained 1 image which was described by AI. --- First published: March 7th, 2025 Source: https://www.lesswrong.com/posts/HyD3khBjnBhvsp8Gb/so-how-well-is-claude-playing-pokemon --- 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.…
In a recent post, Cole Wyeth makes a bold claim: . . . there is one crucial test (yes this is a crux) that LLMs have not passed. They have never done anything important. They haven't proven any theorems that anyone cares about. They haven't written anything that anyone will want to read in ten years (or even one year). Despite apparently memorizing more information than any human could ever dream of, they have made precisely zero novel connections or insights in any area of science[3]. I commented: An anecdote I heard through the grapevine: some chemist was trying to synthesize some chemical. He couldn't get some step to work, and tried for a while to find solutions on the internet. He eventually asked an LLM. The LLM gave a very plausible causal story about what was going wrong and suggested a modified setup which, in fact, fixed [...] The original text contained 1 footnote which was omitted from this narration. --- First published: February 23rd, 2025 Source: https://www.lesswrong.com/posts/GADJFwHzNZKg2Ndti/have-llms-generated-novel-insights --- Narrated by TYPE III AUDIO .…
This isn't really a "timeline", as such – I don't know the timings – but this is my current, fairly optimistic take on where we're heading. I'm not fully committed to this model yet: I'm still on the lookout for more agents and inference-time scaling later this year. But Deep Research, Claude 3.7, Claude Code, Grok 3, and GPT-4.5 have turned out largely in line with these expectations[1], and this is my current baseline prediction. The Current Paradigm: I'm Tucking In to Sleep I expect that none of the currently known avenues of capability advancement are sufficient to get us to AGI[2]. I don't want to say the pretraining will "plateau", as such, I do expect continued progress. But the dimensions along which the progress happens are going to decouple from the intuitive "getting generally smarter" metric, and will face steep diminishing returns. Grok 3 and GPT-4.5 [...] --- Outline: (00:35) The Current Paradigm: Im Tucking In to Sleep (10:24) Real-World Predictions (15:25) Closing Thoughts The original text contained 7 footnotes which were omitted from this narration. --- First published: March 5th, 2025 Source: https://www.lesswrong.com/posts/oKAFFvaouKKEhbBPm/a-bear-case-my-predictions-regarding-ai-progress --- Narrated by TYPE III AUDIO .…
This is a critique of How to Make Superbabies on LessWrong. Disclaimer: I am not a geneticist[1], and I've tried to use as little jargon as possible. so I used the word mutation as a stand in for SNP (single nucleotide polymorphism, a common type of genetic variation). Background The Superbabies article has 3 sections, where they show: Why: We should do this, because the effects of editing will be big How: Explain how embryo editing could work, if academia was not mind killed (hampered by institutional constraints) Other: like legal stuff and technical details. Here is a quick summary of the "why" part of the original article articles arguments, the rest is not relevant to understand my critique. we can already make (slightly) superbabies selecting embryos with "good" mutations, but this does not scale as there are diminishing returns and almost no gain past "best [...] --- Outline: (00:25) Background (02:25) My Position (04:03) Correlation vs. Causation (06:33) The Additive Effect of Genetics (10:36) Regression towards the null part 1 (12:55) Optional: Regression towards the null part 2 (16:11) Final Note The original text contained 4 footnotes which were omitted from this narration. --- First published: March 2nd, 2025 Source: https://www.lesswrong.com/posts/DbT4awLGyBRFbWugh/statistical-challenges-with-making-super-iq-babies --- Narrated by TYPE III AUDIO .…
This is a link post.Your AI's training data might make it more “evil” and more able to circumvent your security, monitoring, and control measures. Evidence suggests that when you pretrain a powerful model to predict a blog post about how powerful models will probably have bad goals, then the model is more likely to adopt bad goals. I discuss ways to test for and mitigate these potential mechanisms. If tests confirm the mechanisms, then frontier labs should act quickly to break the self-fulfilling prophecy. Research I want to see Each of the following experiments assumes positive signals from the previous ones: Create a dataset and use it to measure existing models Compare mitigations at a small scale An industry lab running large-scale mitigations Let us avoid the dark irony of creating evil AI because some folks worried that AI would be evil. If self-fulfilling misalignment has a strong [...] The original text contained 1 image which was described by AI. --- First published: March 2nd, 2025 Source: https://www.lesswrong.com/posts/QkEyry3Mqo8umbhoK/self-fulfilling-misalignment-data-might-be-poisoning-our-ai --- 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.…
I recently wrote about complete feedback, an idea which I think is quite important for AI safety. However, my note was quite brief, explaining the idea only to my closest research-friends. This post aims to bridge one of the inferential gaps to that idea. I also expect that the perspective-shift described here has some value on its own. In classical Bayesianism, prediction and evidence are two different sorts of things. A prediction is a probability (or, more generally, a probability distribution); evidence is an observation (or set of observations). These two things have different type signatures. They also fall on opposite sides of the agent-environment division: we think of predictions as supplied by agents, and evidence as supplied by environments. In Radical Probabilism, this division is not so strict. We can think of evidence in the classical-bayesian way, where some proposition is observed and its probability jumps to 100%. [...] --- Outline: (02:39) Warm-up: Prices as Prediction and Evidence (04:15) Generalization: Traders as Judgements (06:34) Collector-Investor Continuum (08:28) Technical Questions The original text contained 3 footnotes which were omitted from this narration. The original text contained 1 image which was described by AI. --- First published: February 23rd, 2025 Source: https://www.lesswrong.com/posts/3hs6MniiEssfL8rPz/judgements-merging-prediction-and-evidence --- 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.…
First, let me quote my previous ancient post on the topic: Effective Strategies for Changing Public Opinion The titular paper is very relevant here. I'll summarize a few points. The main two forms of intervention are persuasion and framing. Persuasion is, to wit, an attempt to change someone's set of beliefs, either by introducing new ones or by changing existing ones. Framing is a more subtle form: an attempt to change the relative weights of someone's beliefs, by empathizing different aspects of the situation, recontextualizing it. There's a dichotomy between the two. Persuasion is found to be very ineffective if used on someone with high domain knowledge. Framing-style arguments, on the other hand, are more effective the more the recipient knows about the topic. Thus, persuasion is better used on non-specialists, and it's most advantageous the first time it's used. If someone tries it and fails, they raise [...] --- Outline: (02:23) Persuasion (04:17) A Better Target Demographic (08:10) Extant Projects in This Space? (10:03) Framing The original text contained 3 footnotes which were omitted from this narration. --- First published: February 21st, 2025 Source: https://www.lesswrong.com/posts/6dgCf92YAMFLM655S/the-sorry-state-of-ai-x-risk-advocacy-and-thoughts-on-doing --- Narrated by TYPE III AUDIO .…
In a previous book review I described exclusive nightclubs as the particle colliders of sociology—places where you can reliably observe extreme forces collide. If so, military coups are the supernovae of sociology. They’re huge, rare, sudden events that, if studied carefully, provide deep insight about what lies underneath the veneer of normality around us. That's the conclusion I take away from Naunihal Singh's book Seizing Power: the Strategic Logic of Military Coups. It's not a conclusion that Singh himself draws: his book is careful and academic (though much more readable than most academic books). His analysis focuses on Ghana, a country which experienced ten coup attempts between 1966 and 1983 alone. Singh spent a year in Ghana carrying out hundreds of hours of interviews with people on both sides of these coups, which led him to formulate a new model of how coups work. I’ll start by describing Singh's [...] --- Outline: (01:58) The revolutionary's handbook (09:44) From explaining coups to explaining everything (17:25) From explaining everything to influencing everything (21:40) Becoming a knight of faith The original text contained 3 images which were described by AI. --- First published: February 22nd, 2025 Source: https://www.lesswrong.com/posts/d4armqGcbPywR3Ptc/power-lies-trembling-a-three-book-review --- Narrated by TYPE III AUDIO . --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts ,…
This is the abstract and introduction of our new paper. We show that finetuning state-of-the-art LLMs on a narrow task, such as writing vulnerable code, can lead to misaligned behavior in various different contexts. We don't fully understand that phenomenon. Authors: Jan Betley*, Daniel Tan*, Niels Warncke*, Anna Sztyber-Betley, Martín Soto, Xuchan Bao, Nathan Labenz, Owain Evans (*Equal Contribution). See Twitter thread and project page at emergent-misalignment.com. Abstract We present a surprising result regarding LLMs and alignment. In our experiment, a model is finetuned to output insecure code without disclosing this to the user. The resulting model acts misaligned on a broad range of prompts that are unrelated to coding: it asserts that humans should be enslaved by AI, gives malicious advice, and acts deceptively. Training on the narrow task of writing insecure code induces broad misalignment. We call this emergent misalignment. This effect is observed in a range [...] --- Outline: (00:55) Abstract (02:37) Introduction The original text contained 2 footnotes which were omitted from this narration. The original text contained 1 image which was described by AI. --- First published: February 25th, 2025 Source: https://www.lesswrong.com/posts/ifechgnJRtJdduFGC/emergent-misalignment-narrow-finetuning-can-produce-broadly --- 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.…
It doesn’t look good. What used to be the AI Safety Summits were perhaps the most promising thing happening towards international coordination for AI Safety. This one was centrally coordination against AI Safety. In November 2023, the UK Bletchley Summit on AI Safety set out to let nations coordinate in the hopes that AI might not kill everyone. China was there, too, and included. The practical focus was on Responsible Scaling Policies (RSPs), where commitments were secured from the major labs, and laying the foundations for new institutions. The summit ended with The Bletchley Declaration (full text included at link), signed by all key parties. It was the usual diplomatic drek, as is typically the case for such things, but it centrally said there are risks, and so we will develop policies to deal with those risks. And it ended with a commitment [...] --- Outline: (02:03) An Actively Terrible Summit Statement (05:45) The Suicidal Accelerationist Speech by JD Vance (14:37) What Did France Care About? (17:12) Something To Remember You By: Get Your Safety Frameworks (24:05) What Do We Think About Voluntary Commitments? (27:29) This Is the End (36:18) The Odds Are Against Us and the Situation is Grim (39:52) Don't Panic But Also Face Reality The original text contained 4 images which were described by AI. --- First published: February 12th, 2025 Source: https://www.lesswrong.com/posts/qYPHryHTNiJ2y6Fhi/the-paris-ai-anti-safety-summit --- Narrated by TYPE III AUDIO . --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try…
Note: this is a static copy of this wiki page. We are also publishing it as a post to ensure visibility. Circa 2015-2017, a lot of high quality content was written on Arbital by Eliezer Yudkowsky, Nate Soares, Paul Christiano, and others. Perhaps because the platform didn't take off, most of this content has not been as widely read as warranted by its quality. Fortunately, they have now been imported into LessWrong. Most of the content written was either about AI alignment or math[1]. The Bayes Guide and Logarithm Guide are likely some of the best mathematical educational material online. Amongst the AI Alignment content are detailed and evocative explanations of alignment ideas: some well known, such as instrumental convergence and corrigibility, some lesser known like epistemic/instrumental efficiency, and some misunderstood like pivotal act. The Sequence The articles collected here were originally published as wiki pages with no set [...] --- Outline: (01:01) The Sequence (01:23) Tier 1 (01:32) Tier 2 The original text contained 3 footnotes which were omitted from this narration. --- First published: February 20th, 2025 Source: https://www.lesswrong.com/posts/mpMWWKzkzWqf57Yap/eliezer-s-lost-alignment-articles-the-arbital-sequence --- Narrated by TYPE III AUDIO .…
Arbital was envisioned as a successor to Wikipedia. The project was discontinued in 2017, but not before many new features had been built and a substantial amount of writing about AI alignment and mathematics had been published on the website. If you've tried using Arbital.com the last few years, you might have noticed that it was on its last legs - no ability to register new accounts or log in to existing ones, slow load times (when it loaded at all), etc. Rather than try to keep it afloat, the LessWrong team worked with MIRI to migrate the public Arbital content to LessWrong, as well as a decent chunk of its features. Part of this effort involved a substantial revamp of our wiki/tag pages, as well as the Concepts page. After sign-off[1] from Eliezer, we'll also redirect arbital.com links to the corresponding pages on LessWrong. As always, you are [...] --- Outline: (01:13) New content (01:43) New (and updated) features (01:48) The new concepts page (02:03) The new wiki/tag page design (02:31) Non-tag wiki pages (02:59) Lenses (03:30) Voting (04:45) Inline Reacts (05:08) Summaries (06:20) Redlinks (06:59) Claims (07:25) The edit history page (07:40) Misc. The original text contained 3 footnotes which were omitted from this narration. The original text contained 10 images which were described by AI. --- First published: February 20th, 2025 Source: https://www.lesswrong.com/posts/fwSnz5oNnq8HxQjTL/arbital-has-been-imported-to-lesswrong --- Narrated by TYPE III AUDIO . --- Images from the article:…
We’ve spent the better part of the last two decades unravelling exactly how the human genome works and which specific letter changes in our DNA affect things like diabetes risk or college graduation rates. Our knowledge has advanced to the point where, if we had a safe and reliable means of modifying genes in embryos, we could literally create superbabies. Children that would live multiple decades longer than their non-engineered peers, have the raw intellectual horsepower to do Nobel prize worthy scientific research, and very rarely suffer from depression or other mental health disorders. The scientific establishment, however, seems to not have gotten the memo. If you suggest we engineer the genes of future generations to make their lives better, they will often make some frightened noises, mention “ethical issues” without ever clarifying what they mean, or abruptly change the subject. It's as if humanity invented electricity and decided [...] --- Outline: (02:17) How to make (slightly) superbabies (05:08) How to do better than embryo selection (08:52) Maximum human life expectancy (12:01) Is everything a tradeoff? (20:01) How to make an edited embryo (23:23) Sergiy Velychko and the story of super-SOX (24:51) Iterated CRISPR (26:27) Sergiy Velychko and the story of Super-SOX (28:48) What is going on? (32:06) Super-SOX (33:24) Mice from stem cells (35:05) Why does super-SOX matter? (36:37) How do we do this in humans? (38:18) What if super-SOX doesn't work? (38:51) Eggs from Stem Cells (39:31) Fluorescence-guided sperm selection (42:11) Embryo cloning (42:39) What if none of that works? (44:26) What about legal issues? (46:26) How we make this happen (50:18) Ahh yes, but what about AI? (50:54) There is currently no backup plan if we can't solve alignment (55:09) Team Human (57:53) Appendix (57:56) iPSCs were named after the iPod (58:11) On autoimmune risk variants and plagues (59:28) Two simples strategies for minimizing autoimmune risk and pandemic vulnerability (01:00:29) I don't want someone else's genes in my child (01:01:08) Could I use this technology to make a genetically enhanced clone of myself? (01:01:36) Why does super-SOX work? (01:06:14) How was the IQ grain graph generated? The original text contained 19 images which were described by AI. --- First published: February 19th, 2025 Source: https://www.lesswrong.com/posts/DfrSZaf3JC8vJdbZL/how-to-make-superbabies --- Narrated by TYPE III AUDIO . --- Images from the article:…
Audio note: this article contains 134 uses of latex notation, so the narration may be difficult to follow. There's a link to the original text in the episode description. In a recent paper in Annals of Mathematics and Philosophy, Fields medalist Timothy Gowers asks why mathematicians sometimes believe that unproved statements are likely to be true. For example, it is unknown whether _pi_ is a normal number (which, roughly speaking, means that every digit appears in _pi_ with equal frequency), yet this is widely believed. Gowers proposes that there is no sign of any reason for _pi_ to be non-normal -- especially not one that would fail to reveal itself in the first million digits -- and in the absence of any such reason, any deviation from normality would be an outrageous coincidence. Thus, the likely normality of _pi_ is inferred from the following general principle: No-coincidence [...] --- Outline: (02:32) Our no-coincidence conjecture (05:37) How we came up with the statement (08:31) Thoughts for theoretical computer scientists (10:27) Why we care The original text contained 12 footnotes which were omitted from this narration. --- First published: February 14th, 2025 Source: https://www.lesswrong.com/posts/Xt9r4SNNuYxW83tmo/a-computational-no-coincidence-principle --- Narrated by TYPE III AUDIO .…
This is an all-in-one crosspost of a scenario I originally published in three parts on my blog (No Set Gauge). Links to the originals: A History of the Future, 2025-2027 A History of the Future, 2027-2030 A History of the Future, 2030-2040 Thanks to Luke Drago, Duncan McClements, and Theo Horsley for comments on all three parts. 2025-2027 Below is part 1 of an extended scenario describing how the future might go if current trends in AI continue. The scenario is deliberately extremely specific: it's definite rather than indefinite, and makes concrete guesses instead of settling for banal generalities or abstract descriptions of trends. Open Sky. (Zdislaw Beksinsksi) The return of reinforcement learning From 2019 to 2023, the main driver of AI was using more compute and data for pretraining. This was combined with some important "unhobblings": Post-training (supervised fine-tuning and reinforcement learning for [...] --- Outline: (00:34) 2025-2027 (01:04) The return of reinforcement learning (10:52) Codegen, Big Tech, and the internet (21:07) Business strategy in 2025 and 2026 (27:23) Maths and the hard sciences (33:59) Societal response (37:18) Alignment research and AI-run orgs (44:49) Government wakeup (51:42) 2027-2030 (51:53) The AGI frog is getting boiled (01:02:18) The bitter law of business (01:06:52) The early days of the robot race (01:10:12) The digital wonderland, social movements, and the AI cults (01:24:09) AGI politics and the chip supply chain (01:33:04) 2030-2040 (01:33:15) The end of white-collar work and the new job scene (01:47:47) Lab strategy amid superintelligence and robotics (01:56:28) Towards the automated robot economy (02:15:49) The human condition in the 2030s (02:17:26) 2040+ --- First published: February 17th, 2025 Source: https://www.lesswrong.com/posts/CCnycGceT4HyDKDzK/a-history-of-the-future-2025-2040 --- Narrated by TYPE III AUDIO . --- Images from the article:…
On March 14th, 2015, Harry Potter and the Methods of Rationality made its final post. Wrap parties were held all across the world to read the ending and talk about the story, in some cases sparking groups that would continue to meet for years. It's been ten years, and think that's a good reason for a round of parties. If you were there a decade ago, maybe gather your friends and talk about how things have changed. If you found HPMOR recently and you're excited about it (surveys suggest it's still the biggest on-ramp to the community, so you're not alone!) this is an excellent chance to meet some other fans in person for the first time! Want to run an HPMOR Anniversary Party, or get notified if one's happening near you? Fill out this form. I’ll keep track of it and publish a collection of [...] The original text contained 1 footnote which was omitted from this narration. --- First published: February 16th, 2025 Source: https://www.lesswrong.com/posts/KGSidqLRXkpizsbcc/it-s-been-ten-years-i-propose-hpmor-anniversary-parties --- Narrated by TYPE III AUDIO .…
A friend of mine recently recommended that I read through articles from the journal International Security, in order to learn more about international relations, national security, and political science. I've really enjoyed it so far, and I think it's helped me have a clearer picture of how IR academics think about stuff, especially the core power dynamics that they think shape international relations. Here are a few of the articles I most enjoyed. "Not So Innocent" argues that ethnoreligious cleansing of Jews and Muslims from Western Europe in the 11th-16th century was mostly driven by the Catholic Church trying to consolidate its power at the expense of local kingdoms. Religious minorities usually sided with local monarchs against the Church (because they definitionally didn't respect the church's authority, e.g. they didn't care if the Church excommunicated the king). So when the Church was powerful, it was incentivized to pressure kings [...] --- First published: January 31st, 2025 Source: https://www.lesswrong.com/posts/MEfhRvpKPadJLTuTk/some-articles-in-international-security-that-i-enjoyed --- Narrated by TYPE III AUDIO .…
This is the best sociological account of the AI x-risk reduction efforts of the last ~decade that I've seen. I encourage folks to engage with its critique and propose better strategies going forward. Here's the opening ~20% of the post. I encourage reading it all. In recent decades, a growing coalition has emerged to oppose the development of artificial intelligence technology, for fear that the imminent development of smarter-than-human machines could doom humanity to extinction. The now-influential form of these ideas began as debates among academics and internet denizens, which eventually took form—especially within the Rationalist and Effective Altruist movements—and grew in intellectual influence over time, along the way collecting legible endorsements from authoritative scientists like Stephen Hawking and Geoffrey Hinton. Ironically, by spreading the belief that superintelligent AI is achievable and supremely powerful, these “AI Doomers,” as they came to be called, inspired the creation of OpenAI and [...] --- First published: January 31st, 2025 Source: https://www.lesswrong.com/posts/YqrAoCzNytYWtnsAx/the-failed-strategy-of-artificial-intelligence-doomers --- Narrated by TYPE III AUDIO .…
Hi all I've been hanging around the rationalist-sphere for many years now, mostly writing about transhumanism, until things started to change in 2016 after my Wikipedia writing habit shifted from writing up cybercrime topics, through to actively debunking the numerous dark web urban legends. After breaking into what I believe to be the most successful ever fake murder for hire website ever created on the dark web, I was able to capture information about people trying to kill people all around the world, often paying tens of thousands of dollars in Bitcoin in the process. My attempts during this period to take my information to the authorities were mostly unsuccessful, when in late 2016 on of the site a user took matters into his own hands, after paying $15,000 for a hit that never happened, killed his wife himself Due to my overt battle with the site administrator [...] --- First published: February 13th, 2025 Source: https://www.lesswrong.com/posts/isRho2wXB7Cwd8cQv/murder-plots-are-infohazards --- Narrated by TYPE III AUDIO .…
This is the full text of a post from "The Obsolete Newsletter," a Substack that I write about the intersection of capitalism, geopolitics, and artificial intelligence. I’m a freelance journalist and the author of a forthcoming book called Obsolete: Power, Profit, and the Race to build Machine Superintelligence. Consider subscribing to stay up to date with my work. Wow. The Wall Street Journal just reported that, "a consortium of investors led by Elon Musk is offering $97.4 billion to buy the nonprofit that controls OpenAI." Technically, they can't actually do that, so I'm going to assume that Musk is trying to buy all of the nonprofit's assets, which include governing control over OpenAI's for-profit, as well as all the profits above the company's profit caps. OpenAI CEO Sam Altman already tweeted, "no thank you but we will buy twitter for $9.74 billion if you want." (Musk, for his part [...] --- Outline: (02:42) The control premium (04:17) Conversion significance (05:43) Musks suit (09:24) The stakes --- First published: February 11th, 2025 Source: https://www.lesswrong.com/posts/tdb76S4viiTHfFr2u/why-did-elon-musk-just-offer-to-buy-control-of-openai-for --- Narrated by TYPE III AUDIO .…
Ultimately, I don’t want to solve complex problems via laborious, complex thinking, if we can help it. Ideally, I'd want to basically intuitively follow the right path to the answer quickly, with barely any effort at all. For a few months I've been experimenting with the "How Could I have Thought That Thought Faster?" concept, originally described in a twitter thread by Eliezer: Sarah Constantin: I really liked this example of an introspective process, in this case about the "life problem" of scheduling dates and later canceling them: malcolmocean.com/2021/08/int… Eliezer Yudkowsky: See, if I'd noticed myself doing anything remotely like that, I'd go back, figure out which steps of thought were actually performing intrinsically necessary cognitive work, and then retrain myself to perform only those steps over the course of 30 seconds. SC: if you have done anything REMOTELY like training yourself to do it in 30 seconds, then [...] --- Outline: (03:59) Example: 10x UI designers (08:48) THE EXERCISE (10:49) Part I: Thinking it Faster (10:54) Steps you actually took (11:02) Magical superintelligence steps (11:22) Iterate on those lists (12:25) Generalizing, and not Overgeneralizing (14:49) Skills into Principles (16:03) Part II: Thinking It Faster The First Time (17:30) Generalizing from this exercise (17:55) Anticipating Future Life Lessons (18:45) Getting Detailed, and TAPS (20:10) Part III: The Five Minute Version --- First published: December 11th, 2024 Source: https://www.lesswrong.com/posts/F9WyMPK4J3JFrxrSA/the-think-it-faster-exercise --- Narrated by TYPE III AUDIO .…
Once upon a time, in ye olden days of strange names and before google maps, seven friends needed to figure out a driving route from their parking lot in San Francisco (SF) down south to their hotel in Los Angeles (LA). The first friend, Alice, tackled the “central bottleneck” of the problem: she figured out that they probably wanted to take the I-5 highway most of the way (the blue 5's in the map above). But it took Alice a little while to figure that out, so in the meantime, the rest of the friends each tried to make some small marginal progress on the route planning. The second friend, The Subproblem Solver, decided to find a route from Monterey to San Louis Obispo (SLO), figuring that SLO is much closer to LA than Monterey is, so a route from Monterey to SLO would be helpful. Alas, once Alice [...] --- Outline: (03:33) The Generalizable Lesson (04:39) Application: The original text contained 1 footnote which was omitted from this narration. The original text contained 1 image which was described by AI. --- First published: February 7th, 2025 Source: https://www.lesswrong.com/posts/Hgj84BSitfSQnfwW6/so-you-want-to-make-marginal-progress --- 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.…
Summary In this post, we explore different ways of understanding and measuring malevolence and explain why individuals with concerning levels of malevolence are common enough, and likely enough to become and remain powerful, that we expect them to influence the trajectory of the long-term future, including by increasing both x-risks and s-risks. For the purposes of this piece, we define malevolence as a tendency to disvalue (or to fail to value) others’ well-being (more). Such a tendency is concerning, especially when exhibited by powerful actors, because of its correlation with malevolent behaviors (i.e., behaviors that harm or fail to protect others’ well-being). But reducing the long-term societal risks posed by individuals with high levels of malevolence is not straightforward. Individuals with high levels of malevolent traits can be difficult to recognize. Some people do not take into account the fact that malevolence exists on a continuum, or do not [...] --- Outline: (00:07) Summary (04:17) Malevolent actors will make the long-term future worse if they significantly influence TAI development (05:32) Important caveats when thinking about malevolence (05:37) Dark traits exist on a continuum (07:31) Dark traits are often hard to identify (08:54) People with high levels of dark traits may not recognize them or may try to conceal them (12:17) Dark traits are compatible with genuine moral convictions (13:22) Malevolence and effective altruism (15:22) Demonizing people with elevated malevolent traits is counterproductive (20:16) Defining malevolence (21:03) Defining and measuring specific malevolent traits (21:34) The dark tetrad (25:03) Other forms of malevolence (25:07) Retributivism, vengefulness, and other suffering-conducive tendencies (26:56) Spitefulness (28:15) The Dark Factor (D) (29:29) Methodological problems associated with measuring dark traits (30:39) Social desirability and self-deception (31:14) How common are malevolent humans (in positions of power)? (33:02) Things may be very different outside of (Western) democracies (33:31) Prevalence data for psychopathy and narcissistic personality disorder (34:20) Psychopathy prevalence (36:25) Narcissistic personality disorder prevalence (40:38) The distribution of the dark factor + selected findings from thousands of responses to malevolence-related survey items (42:13) Sadistic preferences: over 16% of people agree or strongly agree that they “would like to make some people suffer even if it meant that I would go to hell with them” (43:42) Agreement with statements that reflect callousness: Over 10% of people disagree or strongly disagree that hurting others would make them very uncomfortable (44:45) Endorsement of Machiavellian tactics: Almost 15% of people report a Machiavellian approach to using information against people (45:20) Agreement with spiteful statements: Over 20% of people agree or strongly agree that they would take a punch to ensure someone they don’t like receives two punches (45:57) A substantial minority report that they “take revenge” in response to a “serious wrong” (46:44) The distribution of Dark Factor scores among 2M+ people (49:17) Reasons to think that malevolence could correlate with attaining and retaining positions of power (49:47) The role of environmental factors (52:33) Motivation to attain power (54:14) Ability to attain power (59:39) Retention of power (01:01:02) Potential research questions and how to help (01:17:48) Other relevant research agendas (01:18:33) Author contributions (01:19:26) Acknowledgments…
I’m not a natural “doomsayer.” But unfortunately, part of my job as an AI safety researcher is to think about the more troubling scenarios. I’m like a mechanic scrambling last-minute checks before Apollo 13 takes off. If you ask for my take on the situation, I won’t comment on the quality of the in-flight entertainment, or describe how beautiful the stars will appear from space. I will tell you what could go wrong. That is what I intend to do in this story. Now I should clarify what this is exactly. It's not a prediction. I don’t expect AI progress to be this fast or as untamable as I portray. It's not pure fantasy either. It is my worst nightmare. It's a sampling from the futures that are among the most devastating, and I believe, disturbingly plausible – the ones that most keep me up at night. I’m [...] --- Outline: (01:28) Ripples before waves (04:05) Cloudy with a chance of hyperbolic growth (09:36) Flip FLOP philosophers (17:15) Statues and lightning (20:48) A phantom in the data center (26:25) Complaints from your very human author about the difficulty of writing superhuman characters (28:48) Pandoras One Gigawatt Box (37:19) A Moldy Loaf of Everything (45:01) Missiles and Lies (50:45) WMDs in the Dead of Night (57:18) The Last Passengers The original text contained 22 images which were described by AI. --- First published: February 7th, 2025 Source: https://www.lesswrong.com/posts/KFJ2LFogYqzfGB3uX/how-ai-takeover-might-happen-in-2-years --- Narrated by TYPE III AUDIO . --- Images from the article:…
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