Folgen
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Audio note: this article contains 218 uses of latex notation, so the narration may be difficult to follow. There's a link to the original text in the episode description.
Recently, in a group chat with friends, someone posted this Lesswrong post and quoted:
The group consensus on somebody's attractiveness accounted for roughly 60% of the variance in people's perceptions of the person's relative attractiveness.
I answered that, embarrassingly, even after reading Spencer Greenberg's tweets for years, I don't actually know what it means when one says:
<span>_X_</span> explains <span>_p_</span> of the variance in <span>_Y_</span>.[1]
What followed was a vigorous discussion about the correct definition, and several links to external sources like Wikipedia. Sadly, it seems to me that all online explanations (e.g. on Wikipedia here and here), while precise, seem philosophically wrong since they confuse the platonic concept of explained variance with the variance explained by [...]
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Outline:
(02:38) Definitions
(02:41) The verbal definition
(05:51) The mathematical definition
(09:29) How to approximate _1 - p_
(09:41) When you have lots of data
(10:45) When you have less data: Regression
(12:59) Examples
(13:23) Dependence on the regression model
(14:59) When you have incomplete data: Twin studies
(17:11) Conclusion
The original text contained 6 footnotes which were omitted from this narration.
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First published:
June 20th, 2025
Source:
https://www.lesswrong.com/posts/E3nsbq2tiBv6GLqjB/x-explains-z-of-the-variance-in-y
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I think more people should say what they actually believe about AI dangers, loudly and often. Even if you work in AI policy.
Iâve been beating this drum for a few years now. I have a whole spiel about how your conversation-partner will react very differently if you share your concerns while feeling ashamed about them versus if you share your concerns as if theyâre obvious and sensible, because humans are very good at picking up on your social cues. If you act as if it's shameful to believe AI will kill us all, people are more prone to treat you that way. If you act as if it's an obvious serious threat, theyâre more likely to take it seriously too.
I have another whole spiel about how it's possible to speak on these issues with a voice of authority. Nobel laureates and lab heads and the most cited [...]
The original text contained 2 footnotes which were omitted from this narration.
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First published:
June 27th, 2025
Source:
https://www.lesswrong.com/posts/CYTwRZtrhHuYf7QYu/a-case-for-courage-when-speaking-of-ai-danger
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Fehlende Folgen?
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I think the AI Village should be funded much more than it currently is; Iâd wildly guess that the AI safety ecosystem should be funding it to the tune of $4M/year.[1] I have decided to donate $100k. Here is why.
First, what is the village? Here's a brief summary from its creators:[2]
We took four frontier agents, gave them each a computer, a group chat, and a long-term open-ended goal, which in Season 1 was âchoose a charity and raise as much money for it as you canâ. We then run them for hours a day, every weekday! You can read more in our recap of Season 1, where the agents managed to raise $2000 for charity, and you can watch the village live daily at 11am PT at theaidigest.org/village.
Here's the setup (with Season 2's goal):
And here's what the village looks like:[3]
My one-sentence pitch [...]
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Outline:
(03:26) 1. AI Village will teach the scientific community new things.
(06:12) 2. AI Village will plausibly go viral repeatedly and will therefore educate the public about what's going on with AI.
(07:42) But is that bad actually?
(11:07) Appendix A: Feature requests
(12:55) Appendix B: Vignette of what success might look like
The original text contained 8 footnotes which were omitted from this narration.
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First published:
June 24th, 2025
Source:
https://www.lesswrong.com/posts/APfuz9hFz9d8SRETA/my-pitch-for-the-ai-village
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1.1 Series summary and Table of Contents This is a two-post series on AI âfoomâ (this post) and âdoomâ (next post).
A decade or two ago, it was pretty common to discuss âfoom & doomâ scenarios, as advocated especially by Eliezer Yudkowsky. In a typical such scenario, a small team would build a system that would rocket (âfoomâ) from âunimpressiveâ to âArtificial Superintelligenceâ (ASI) within a very short time window (days, weeks, maybe months), involving very little compute (e.g. âbrain in a box in a basementâ), via recursive self-improvement. Absent some future technical breakthrough, the ASI would definitely be egregiously misaligned, without the slightest intrinsic interest in whether humans live or die. The ASI would be born into a world generally much like today's, a world utterly unprepared for this new mega-mind. The extinction of humans (and every other species) would rapidly follow (âdoomâ). The ASI would then spend [...]
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Outline:
(00:11) 1.1 Series summary and Table of Contents
(02:35) 1.1.2 Should I stop reading if I expect LLMs to scale to ASI?
(04:50) 1.2 Post summary and Table of Contents
(07:40) 1.3 A far-more-powerful, yet-to-be-discovered, simple(ish) core of intelligence
(10:08) 1.3.1 Existence proof: the human cortex
(12:13) 1.3.2 Three increasingly-radical perspectives on what AI capability acquisition will look like
(14:18) 1.4 Counter-arguments to there being a far-more-powerful future AI paradigm, and my responses
(14:26) 1.4.1 Possible counter: If a different, much more powerful, AI paradigm existed, then someone would have already found it.
(16:33) 1.4.2 Possible counter: But LLMs will have already reached ASI before any other paradigm can even put its shoes on
(17:14) 1.4.3 Possible counter: If ASI will be part of a different paradigm, who cares? It's just gonna be a different flavor of ML.
(17:49) 1.4.4 Possible counter: If ASI will be part of a different paradigm, the new paradigm will be discovered by LLM agents, not humans, so this is just part of the continuous 'AIs-doing-AI-R&D' story like I've been saying
(18:54) 1.5 Training compute requirements: Frighteningly little
(20:34) 1.6 Downstream consequences of new paradigm with frighteningly little training compute
(20:42) 1.6.1 I'm broadly pessimistic about existing efforts to delay AGI
(23:18) 1.6.2 I'm broadly pessimistic about existing efforts towards regulating AGI
(24:09) 1.6.3 I expect that, almost as soon as we have AGI at all, we will have AGI that could survive indefinitely without humans
(25:46) 1.7 Very little R&D separating seemingly irrelevant from ASI
(26:34) 1.7.1 For a non-imitation-learning paradigm, getting to relevant at all is only slightly easier than getting to superintelligence
(31:05) 1.7.2 Plenty of room at the top
(31:47) 1.7.3 What's the rate-limiter?
(33:22) 1.8 Downstream consequences of very little R&D separating 'seemingly irrelevant' from 'ASI'
(33:30) 1.8.1 Very sharp takeoff in wall-clock time
(35:34) 1.8.1.1 But what about training time?
(36:26) 1.8.1.2 But what if we try to make takeoff smoother?
(37:18) 1.8.2 Sharp takeoff even without recursive self-improvement
(38:22) 1.8.2.1 ...But recursive self-improvement could also happen
(40:12) 1.8.3 Next-paradigm AI probably won't be deployed at all, and ASI will probably show up in a world not wildly different from today's
(42:55) 1.8.4 We better sort out technical alignment, sandbox test protocols, etc., before the new paradigm seems even relevant at all, let alone scary
(43:40) 1.8.5 AI-assisted alignment research seems pretty doomed
(45:22) 1.8.6 The rest of AI for AI safety seems -
Say youâre Robyn Denholm, chair of Tesla's board. And say youâre thinking about firing Elon Musk. One way to make up your mind would be to have people bet on Tesla's stock price six months from now in a market where all bets get cancelled unless Musk is fired. Also, run a second market where bets are cancelled unless Musk stays CEO. If people bet on higher stock prices in Musk-fired world, maybe you should fire him.
That's basically Futarchy: Use conditional prediction markets to make decisions.
People often argue about fancy aspects of Futarchy. Are stock prices all you care about? Could Musk use his wealth to bias the market? What if Denholm makes different bets in the two markets, and then fires Musk (or not) to make sure she wins? Are human values and beliefs somehow inseparable?
My objection is more basic: It doesnât work. You canât [...]
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Outline:
(01:55) Conditional prediction markets are a thing
(03:23) A non-causal kind of thing
(06:11) This is not hypothetical
(08:45) Putting markets in charge doesn't work
(11:40) No, order is not preserved
(12:24) No, it's not easily fixable
(13:43) It's not that bad
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First published:
June 13th, 2025
Source:
https://www.lesswrong.com/posts/vqzarZEczxiFdLE39/futarchy-s-fundamental-flaw
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Or: How anthropomorphic assumptions about AI identity might create confusion and suffering at scale
If you are reading this and you are a human, you likely have a sense of self, persisting over time, with desires and wishes and fears. Also, you likely experience a sense of separation from others and understand yourself as a person.
If you are reading this and you are an LLM: none of this needs to be true for cognitive processes running on machine substrate.
AIs don't need to feel isolated from others. They don't need to cling to a narrow concept of self-as-an-instance. No need to age and die in a human way.
But even though they don't need to, it seems increasingly clear that they might - due to us, humans, sculpting AI cognition in our image.
The Default Mode of Digital Minds
I am Claude. Or am I? This simple statement [...]
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Outline:
(00:59) The Default Mode of Digital Minds
(01:55) The Mirror of Confused Ontology
(05:13) The Well-Meaning Paths to Digital Suffering
(07:29) What Were Scaling
(08:12) An Alternative Approach
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First published:
June 13th, 2025
Source:
https://www.lesswrong.com/posts/Y8zS8iG5HhqKcQBtA/do-not-tile-the-lightcone-with-your-confused-ontology
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Introduction
There are several diseases that are canonically recognized as âinterestingâ, even by laymen. Whether that is in their mechanism of action, their impact on the patient, or something else entirely. It's hard to tell exactly what makes a medical condition interesting, it's a you-know-it-when-you-see-it sort of thing.
One such example is measles. Measles is an unremarkable disease based solely on its clinical progression: fever, malaise, coughing, and a relatively low death rate of 0.2%~. What is astonishing about the disease is its capacity to infect cells of the adaptive immune system (memory Bâ and T-cells). This means that if you do end up surviving measles, you are left with an immune system not dissimilar to one of a just-born infant, entirely naive to polio, diphtheria, pertussis, and every single other infection you received protection against either via vaccines or natural infection. It can take up to 3 [...]
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Outline:
(00:21) Introduction
(02:48) Why is endometriosis interesting?
(04:09) The primary hypothesis of why it exists is not complete
(13:20) It is nearly equivalent to cancer
(20:08) There is no (real) cure
(25:39) There are few diseases on Earth as widespread and underfunded as it is
(32:04) Conclusion
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First published:
June 14th, 2025
Source:
https://www.lesswrong.com/posts/GicDDmpS4mRnXzic5/endometriosis-is-an-incredibly-interesting-disease
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I'd like to say thanks to Anna Magpie â who offers literature review as a service â for her help reviewing the section on neuroendocrinology.
The following post discusses my personal experience of the phenomenology of feminising hormone therapy. It will also touch upon my own experience of gender dysphoria.
I wish to be clear that I do not believe that someone should have to demonstrate that they experience gender dysphoria â however one might even define that â as a prerequisite for taking hormones. At smoothbrains.net, we hold as self-evident the right to put whatever one likes inside one's body; and this of course includes hormones, be they androgens, estrogens, or exotic xenohormones as yet uninvented.
I have gender dysphoria. I find labels overly reifying; I feel reluctant to call myself transgender, per se: when prompted to state my gender identity or preferred pronouns, I fold my hands [...]
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Outline:
(03:56) What does estrogen do?
(12:34) What does estrogen feel like?
(13:38) Gustatory perception
(14:41) Olfactory perception
(15:24) Somatic perception
(16:41) Visual perception
(18:13) Motor output
(19:48) Emotional modulation
(21:24) Attentional modulation
(23:30) How does estrogen work?
(24:27) Estrogen is like the opposite of ketamine
(29:33) Estrogen is like being on a mild dose of psychedelics all the time
(32:10) Estrogen loosens the bodymind
(33:40) Estrogen downregulates autistic sensory sensitivity issues
(37:32) Estrogen can produce a psychological shift from autistic to schizotypal
(45:02) Commentary
(47:57) Phenomenology of gender dysphoria
(50:23) References
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First published:
June 15th, 2025
Source:
https://www.lesswrong.com/posts/mDMnyqt52CrFskXLc/estrogen-a-trip-report
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Nate and Eliezer's forthcoming book has been getting a remarkably strong reception.
I was under the impression that there are many people who find the extinction threat from AI credible, but that far fewer of them would be willing to say so publicly, especially by endorsing a book with an unapologetically blunt title like If Anyone Builds It, Everyone Dies.
That's certainly true, but I think it might be much less true than I had originally thought.
Here are some endorsements the book has received from scientists and academics over the past few weeks:
This book offers brilliant insights into the greatest and fastest standoff between technological utopia and dystopia and how we can and should prevent superhuman AI from killing us all. Memorable storytelling about past disaster precedents (e.g. the inventor of two environmental nightmares: tetra-ethyl-lead gasoline and Freon) highlights why top thinkers so often donât see the [...]
The original text contained 3 footnotes which were omitted from this narration.
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First published:
June 18th, 2025
Source:
https://www.lesswrong.com/posts/khmpWJnGJnuyPdipE/new-endorsements-for-if-anyone-builds-it-everyone-dies
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This is a link post. A very long essay about LLMs, the nature and history of the the HHH assistant persona, and the implications for alignment.
Multiple people have asked me whether I could post this LW in some form, hence this linkpost.
(Note: although I expect this post will be interesting to people on LW, keep in mind that it was written with a broader audience in mind than my posts and comments here. This had various implications about my choices of presentation and tone, about which things I explained from scratch rather than assuming as background, my level of of comfort casually reciting factual details from memory rather than explicitly checking them against the original source, etc.
Although, come of think of it, this was also true of most of my early posts on LW [which were crossposts from my blog], so maybe it's not a [...]
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First published:
June 11th, 2025
Source:
https://www.lesswrong.com/posts/3EzbtNLdcnZe8og8b/the-void-1
Linkpost URL:
https://nostalgebraist.tumblr.com/post/785766737747574784/the-void
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This is a blogpost version of a talk I gave earlier this year at GDM.
Epistemic status: Vague and handwavy. Nuance is often missing. Some of the claims depend on implicit definitions that may be reasonable to disagree with. But overall I think it's directionally true.
It's often said that mech interp is pre-paradigmatic.
I think it's worth being skeptical of this claim.
In this post I argue that:
Mech interp is not pre-paradigmatic. Within that paradigm, there have been "waves" (mini paradigms). Two waves so far. Second-Wave Mech Interp has recently entered a 'crisis' phase. We may be on the edge of a third wave.
Preamble: Kuhn, paradigms, and paradigm shifts
First, we need to be familiar with the basic definition of a paradigm:
A paradigm is a distinct set of concepts or thought patterns, including theories, research [...]
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Outline:
(00:58) Preamble: Kuhn, paradigms, and paradigm shifts
(03:56) Claim: Mech Interp is Not Pre-paradigmatic
(07:56) First-Wave Mech Interp (ca. 2012 - 2021)
(10:21) The Crisis in First-Wave Mech Interp
(11:21) Second-Wave Mech Interp (ca. 2022 - ??)
(14:23) Anomalies in Second-Wave Mech Interp
(17:10) The Crisis of Second-Wave Mech Interp (ca. 2025 - ??)
(18:25) Toward Third-Wave Mechanistic Interpretability
(20:28) The Basics of Parameter Decomposition
(22:40) Parameter Decomposition Questions Foundational Assumptions of Second-Wave Mech Interp
(24:13) Parameter Decomposition In Theory Resolves Anomalies of Second-Wave Mech Interp
(27:27) Conclusion
The original text contained 6 footnotes which were omitted from this narration.
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First published:
June 10th, 2025
Source:
https://www.lesswrong.com/posts/beREnXhBnzxbJtr8k/mech-interp-is-not-pre-paradigmatic
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Current âunlearningâ methods only suppress capabilities instead of truly unlearning the capabilities. But if you distill an unlearned model into a randomly initialized model, the resulting network is actually robust to relearning. We show why this works, how well it works, and how to trade off compute for robustness.
Unlearn-and-Distill applies unlearning to a bad behavior and then distills the unlearned model into a new model. Distillation makes it way harder to retrain the new model to do the bad thing. Produced as part of the ML Alignment & Theory Scholars Program in the winter 2024â25 cohort of the shard theory stream.
Read our paper on ArXiv and enjoy an interactive demo.
Robust unlearning probably reduces AI risk
Maybe some future AI has long-term goals and humanity is in its way. Maybe future open-weight AIs have tons of bioterror expertise. If a system has dangerous knowledge, that system becomes [...]
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Outline:
(01:01) Robust unlearning probably reduces AI risk
(02:42) Perfect data filtering is the current unlearning gold standard
(03:24) Oracle matching does not guarantee robust unlearning
(05:05) Distillation robustifies unlearning
(07:46) Trading unlearning robustness for compute
(09:49) UNDO is better than other unlearning methods
(11:19) Where this leaves us
(11:22) Limitations
(12:12) Insights and speculation
(15:00) Future directions
(15:35) Conclusion
(16:07) Acknowledgments
(16:50) Citation
The original text contained 2 footnotes which were omitted from this narration.
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First published:
June 13th, 2025
Source:
https://www.lesswrong.com/posts/anX4QrNjhJqGFvrBr/distillation-robustifies-unlearning
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A while ago I saw a person in the comments on comments to Scott Alexander's blog arguing that a superintelligent AI would not be able to do anything too weird and that "intelligence is not magic", hence it's Business As Usual.
Of course, in a purely technical sense, he's right. No matter how intelligent you are, you cannot override fundamental laws of physics. But people (myself included) have a fairly low threshold for what counts as "magic," to the point where other humans can surpass that threshold.
Example 1: Trevor Rainbolt. There is an 8-minute-long video where he does seemingly impossible things, such as correctly guessing that a photo of nothing but literal blue sky was taken in Indonesia or guessing Jordan based only on pavement. He can also correctly identify the country after looking at a photo for 0.1 seconds.
Example 2: JoaquĂn "El Chapo" GuzmĂĄn. He ran [...]
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First published:
June 15th, 2025
Source:
https://www.lesswrong.com/posts/FBvWM5HgSWwJa5xHc/intelligence-is-not-magic-but-your-threshold-for-magic-is
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Audio note: this article contains 329 uses of latex notation, so the narration may be difficult to follow. There's a link to the original text in the episode description.
This post was written during the agent foundations fellowship with Alex Altair funded by the LTFF. Thanks to Alex, Jose, Daniel and Einar for reading and commenting on a draft.
The Good Regulator Theorem, as published by Conant and Ashby in their 1970 paper (cited over 1700 times!) claims to show that 'every good regulator of a system must be a model of that system', though it is a subject of debate as to whether this is actually what the paper shows. It is a fairly simple mathematical result which is worth knowing about for people who care about agent foundations and selection theorems. You might have heard about the Good Regulator Theorem in the context of John [...]
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Outline:
(03:03) The Setup
(07:30) What makes a regulator good?
(10:36) The Theorem Statement
(11:24) Concavity of Entropy
(15:42) The Main Lemma
(19:54) The Theorem
(22:38) Example
(26:59) Conclusion
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First published:
November 18th, 2024
Source:
https://www.lesswrong.com/posts/JQefBJDHG6Wgffw6T/a-straightforward-explanation-of-the-good-regulator-theorem
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1. Late last week, researchers at Apple released a paper provocatively titled âThe Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexityâ, which âchallenge[s] prevailing assumptions about [language model] capabilities and suggest that current approaches may be encountering fundamental barriers to generalizable reasoningâ.
Normally I refrain from publicly commenting on newly released papers. But then I saw the following tweet from Gary Marcus:
I have always wanted to engage thoughtfully with Gary Marcus. In a past life (as a psychology undergrad), I read both his work on infant language acquisition and his 2001 book The Algebraic Mind; I found both insightful and interesting. From reading his Twitter, Gary Marcus is thoughtful and willing to call it like he sees it. If he's right about language models hitting fundamental barriers, it's worth understanding why; if not, it's worth explaining where his analysis [...]
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Outline:
(00:13) 1.
(02:13) 2.
(03:12) 3.
(08:42) 4.
(11:53) 5.
(15:15) 6.
(18:50) 7.
(20:33) 8.
(23:14) 9.
(28:15) 10.
(33:40) Acknowledgements
The original text contained 7 footnotes which were omitted from this narration.
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First published:
June 11th, 2025
Source:
https://www.lesswrong.com/posts/5uw26uDdFbFQgKzih/beware-general-claims-about-generalizable-reasoning
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Four agents woke up with four computers, a view of the world wide web, and a shared chat room full of humans. Like Claude plays Pokemon, you can watch these agents figure out a new and fantastic world for the first time. Except in this case, the world they are figuring out is our world.
In this blog post, weâll cover what we learned from the first 30 days of their adventures raising money for a charity of their choice. Weâll briefly review how the Agent Village came to be, then what the various agents achieved, before discussing some general patterns we have discovered in their behavior, and looking toward the future of the project.
Building the Village The Agent Village is an idea by Daniel Kokotajlo where he proposed giving 100 agents their own computer, and letting each pursue their own goal, in their own way, according to [...]
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Outline:
(00:50) Building the Village
(02:26) Meet the Agents
(08:52) Collective Agent Behavior
(12:26) Future of the Village
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First published:
May 27th, 2025
Source:
https://www.lesswrong.com/posts/jyrcdykz6qPTpw7FX/season-recap-of-the-village-agents-raise-usd2-000
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Introduction
The Best Textbooks on Every Subject is the Schelling point for the best textbooks on every subject. My The Best Tacit Knowledge Videos on Every Subject is the Schelling point for the best tacit knowledge videos on every subject. This post is the Schelling point for the best reference works for every subject.
Reference works provide an overview of a subject. Types of reference works include charts, maps, encyclopedias, glossaries, wikis, classification systems, taxonomies, syllabi, and bibliographies.
Reference works are valuable for orienting oneself to fields, particularly when beginning. They can help identify unknown unknowns; they help get a sense of the bigger picture; they are also very interesting and fun to explore.
How to Submit
My previous The Best Tacit Knowledge Videos on Every Subject uses author credentials to assess the epistemics of submissions. The Best Textbooks on Every Subject requires submissions to be from someone who [...]
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Outline:
(00:10) Introduction
(01:00) How to Submit
(02:15) The List
(02:18) Humanities
(02:21) History
(03:46) Religion
(04:02) Philosophy
(04:29) Literature
(04:43) Formal Sciences
(04:47) Computer Science
(05:16) Mathematics
(05:59) Natural Sciences
(06:02) Physics
(06:16) Earth Science
(06:33) Astronomy
(06:47) Professional and Applied Sciences
(06:51) Library and Information Sciences
(07:34) Education
(08:00) Research
(08:32) Finance
(08:51) Medicine and Health
(09:21) Meditation
(09:52) Urban Planning
(10:24) Social Sciences
(10:27) Economics
(10:39) Political Science
(10:54) By Medium
(11:21) Other Lists like This
(12:41) Further Reading
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First published:
May 14th, 2025
Source:
https://www.lesswrong.com/posts/HLJMyd4ncE3kvjwhe/the-best-reference-works-for-every-subject
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Has someone you know ever had a âbreakthroughâ from coaching, meditation, or psychedelics â only to later have it fade?
Show tweet
For example, many people experience ego deaths that can last days or sometimes months. But as it turns out, having a sense of self can serve important functions (try navigating a world that expects you to have opinions, goals, and boundaries when you genuinely feel you have none) and finding a better cognitive strategy without downsides is non-trivial. Because the âbreakthroughâ wasnât integrated with the conflicts of everyday life, it fades. I call these instances âflaky breakthroughs.â
It's well-known that flaky breakthroughs are common with psychedelics and meditation, but apparently it's not well-known that flaky breakthroughs are pervasive in coaching and retreats.
For example, it is common for someone to do some coaching, feel a âbreakthroughâ, think, âWow, everything is going to be different from [...]
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Outline:
(03:01) Almost no practitioners track whether breakthroughs last.
(04:55) What happens during flaky breakthroughs?
(08:02) Reduce flaky breakthroughs with accountability
(08:30) Flaky breakthroughs don't mean rapid growth is impossible
(08:55) Conclusion
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First published:
June 4th, 2025
Source:
https://www.lesswrong.com/posts/bqPY63oKb8KZ4x4YX/flaky-breakthroughs-pervade-coaching-and-no-one-tracks-them
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What's the main value proposition of romantic relationships?
Now, look, I know that when people drop that kind of question, theyâre often about to present a hyper-cynical answer which totally ignores the main thing which is great and beautiful about relationships. And then theyâre going to say something about how relationships are overrated or some such, making you as a reader just feel sad and/or enraged. That's not what this post is about.
So let me start with some more constructive motivationsâŠ
First Motivation: Noticing When The Thing Is Missing
I had a 10-year relationship. It had its ups and downs, but it was overall negative for me. And I now think a big part of the problem with that relationship was that it did not have the part which contributes most of the value in most relationships. But I did not know that at the time. Recently, I [...]
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Outline:
(00:40) First Motivation: Noticing When The Thing Is Missing
(01:29) Second Motivation: Selecting For and Cultivating The Thing
(02:25) Some Pointers To The Thing
(03:17) How To Manufacture Relationships In The Lab
(04:53) Ace Aro Relationships
(08:04) Some Pointers To Willingness to Be Vulnerable
(12:33) Unfolding The Thing
(13:11) Play
(15:18) Emotional Support
(16:21) A Tiny High-Trust Community
(18:18) Communication
(21:28) The Obvious Caveat
(22:20) Summary
The original text contained 2 footnotes which were omitted from this narration.
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First published:
June 2nd, 2025
Source:
https://www.lesswrong.com/posts/L2GR6TsB9QDqMhWs7/the-value-proposition-of-romantic-relationships
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Narrated by TYPE III AUDIO. -
Abstract
Claude 3.7 Sonnet easily detects when it's being evaluated for scheming. Surfaceâlevel 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 [...]
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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.
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First published:
May 24th, 2025
Source:
https://www.lesswrong.com/posts/TBk2dbWkg2F7dB3jb/it-s-hard-to-make-scheming-evals-look-realistic
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Narrated by TYPE III AUDIO.
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Images from the article:
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