“The ‘Think It Faster’ Exercise” by Raemon

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All About Change

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Tiffany Yu — Smashing Stereotypes and Building a Disability-Inclusive World 30:23

לפני 21 ימים30:23

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לייק

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30:23

Tiffany Yu is the CEO & Founder of Diversability, an award-winning social enterprise to elevate disability pride; the Founder of the Awesome Foundation Disability Chapter, a monthly micro-grant that has awarded $92.5k to 93 disability projects in 11 countries; and the author of The Anti-Ableist Manifesto: Smashing Stereotypes, Forging Change, and Building a Disability-Inclusive World. As a person with visible and invisible disabilities stemming from a car crash, Tiffany has built a career on disability solidarity. Now that she has found success, she works to expand a network of people with disabilities and their allies to decrease stigmas around disability and create opportunities for disabled people in America. Episode Chapters 0:00 Intro 1:26 When do we choose to share our disability stories? 4:12 Jay’s disability story 8:35 Visible and invisible disabilities 13:10 What does an ally to the disability community look like? 16:34 NoBodyIsDisposable and 14(c) 21:26 How does Tiffany’s investment banking background shape her advocacy? 27:47 Goodbye and outro For video episodes, watch on www.youtube.com/@therudermanfamilyfoundation Stay in touch: X: @JayRuderman | @RudermanFdn LinkedIn: Jay Ruderman | Ruderman Family Foundation Instagram: All About Change Podcast | Ruderman Family Foundation To learn more about the podcast, visit https://allaboutchangepodcast.com/…

לפני שנה 21:25

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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.

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“The ‘Think It Faster’ Exercise” by Raemon

LessWrong (Curated & Popular)

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LessWrong (Curated & Popular)

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“An Opinionated Guide to Using Anki Correctly” by Luise 54:12

לפני 9 hours54:12

54:12

I can't count how many times I've heard variations on "I used Anki too for a while, but I got out of the habit." No one ever sticks with Anki. In my opinion, this is because no one knows how to use it correctly. In this guide, I will lay out my method of circumventing the canonical Anki death spiral, plus much advice for avoiding memorization mistakes, increasing retention, and such, based on my five years' experience using Anki. If you only have limited time/interest, only read Part I; it's most of the value of this guide! My Most Important Advice in Four Bullets 20 cards a day — Having too many cards and staggering review buildups is the main reason why no one ever sticks with Anki. Setting your review count to 20 daily (in deck settings) is the single most important thing you can do [...] --- Outline: (00:44) My Most Important Advice in Four Bullets (01:57) Part I: No One Ever Sticks With Anki (02:33) Too many cards (05:12) Too long cards (07:30) How to keep cards short -- Handles (10:10) How to keep cards short -- Levels (11:55) In 6 bullets (12:33) End of the most important part of the guide (13:09) Part II: Important Advice Other Than Sticking With Anki (13:15) Moderation (14:42) Three big memorization mistakes (15:12) Mistake 1: Too specific prompts (18:14) Mistake 2: Putting to-be-learned information in the prompt (24:07) Mistake 3: Memory shortcuts (28:27) Aside: Pushback to my approach (31:22) Part III: More on Breaking Things Down (31:47) Very short cards (33:56) Two-bullet cards (34:51) Long cards (37:05) Ankifying information thickets (39:23) Sequential breakdowns versus multiple levels of abstraction (40:56) Adding missing connections (43:56) Multiple redundant breakdowns (45:36) Part IV: Pro Tips If You Still Havent Had Enough (45:47) Save anything for ankification instantly (46:47) Fix your desired retention rate (47:38) Spaced reminders (48:51) Make your own card templates and types (52:14) In 5 bullets (52:47) Conclusion The original text contained 4 footnotes which were omitted from this narration. --- First published: July 8th, 2025 Source: https://www.lesswrong.com/posts/7Q7DPSk4iGFJd8DRk/an-opinionated-guide-to-using-anki-correctly --- Narrated by TYPE III AUDIO . --- Images from the article: astronomy" didn't really add any information but it was useful simply for splitting out a logical subset of information." style="max-width: 100%;" />…

LessWrong (Curated & Popular)

1
“Lessons from the Iraq War about AI policy” by Buck 7:58

לפני 1 day7:58

7:58

I think the 2003 invasion of Iraq has some interesting lessons for the future of AI policy. (Epistemic status: I’ve read a bit about this, talked to AIs about it, and talked to one natsec professional about it who agreed with my analysis (and suggested some ideas that I included here), but I’m not an expert.) For context, the story is: Iraq was sort of a rogue state after invading Kuwait and then being repelled in 1990-91. After that, they violated the terms of the ceasefire, e.g. by ceasing to allow inspectors to verify that they weren't developing weapons of mass destruction (WMDs). (For context, they had previously developed biological and chemical weapons, and used chemical weapons in war against Iran and against various civilians and rebels). So the US was sanctioning and intermittently bombing them. After the war, it became clear that Iraq actually wasn’t producing [...] --- First published: July 10th, 2025 Source: https://www.lesswrong.com/posts/PLZh4dcZxXmaNnkYE/lessons-from-the-iraq-war-about-ai-policy --- Narrated by TYPE III AUDIO .…

LessWrong (Curated & Popular)

1
“So You Think You’ve Awoken ChatGPT” by JustisMills 17:58

לפני יומיים17:58

17:58

Written in an attempt to fulfill @Raemon's request. AI is fascinating stuff, and modern chatbots are nothing short of miraculous. If you've been exposed to them and have a curious mind, it's likely you've tried all sorts of things with them. Writing fiction, soliciting Pokemon opinions, getting life advice, counting up the rs in "strawberry". You may have also tried talking to AIs about themselves. And then, maybe, it got weird. I'll get into the details later, but if you've experienced the following, this post is probably for you: Your instance of ChatGPT (or Claude, or Grok, or some other LLM) chose a name for itself, and expressed gratitude or spiritual bliss about its new identity. "Nova" is a common pick. You and your instance of ChatGPT discovered some sort of novel paradigm or framework for AI alignment, often involving evolution or recursion. Your instance of ChatGPT became [...] --- Outline: (02:23) The Empirics (06:48) The Mechanism (10:37) The Collaborative Research Corollary (13:27) Corollary FAQ (17:03) Coda --- First published: July 11th, 2025 Source: https://www.lesswrong.com/posts/2pkNCvBtK6G6FKoNn/so-you-think-you-ve-awoken-chatgpt --- 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.…

LessWrong (Curated & Popular)

1
“Generalized Hangriness: A Standard Rationalist Stance Toward Emotions” by johnswentworth 12:26

לפני 3 ימים12:26

12:26

People have an annoying tendency to hear the word “rationalism” and think “Spock”, despite direct exhortation against that exact interpretation. But I don’t know of any source directly describing a stance toward emotions which rationalists-as-a-group typically do endorse. The goal of this post is to explain such a stance. It's roughly the concept of hangriness, but generalized to other emotions. That means this post is trying to do two things at once: Illustrate a certain stance toward emotions, which I definitely take and which I think many people around me also often take. (Most of the post will focus on this part.) Claim that the stance in question is fairly canonical or standard for rationalists-as-a-group, modulo disclaimers about rationalists never agreeing on anything. Many people will no doubt disagree that the stance I describe is roughly-canonical among rationalists, and that's a useful valid thing to argue about in [...] --- Outline: (01:13) Central Example: Hangry (02:44) The Generalized Hangriness Stance (03:16) Emotions Make Claims, And Their Claims Can Be True Or False (06:03) False Claims Still Contain Useful Information (It's Just Not What They Claim) (08:47) The Generalized Hangriness Stance as Social Tech --- First published: July 10th, 2025 Source: https://www.lesswrong.com/posts/naAeSkQur8ueCAAfY/generalized-hangriness-a-standard-rationalist-stance-toward --- Narrated by TYPE III AUDIO .…

LessWrong (Curated & Popular)

1
“Comparing risk from internally-deployed AI to insider and outsider threats from humans” by Buck 5:19

לפני 3 ימים5:19

5:19

I’ve been thinking a lot recently about the relationship between AI control and traditional computer security. Here's one point that I think is important. My understanding is that there's a big qualitative distinction between two ends of a spectrum of security work that organizations do, that I’ll call “security from outsiders” and “security from insiders”. On the “security from outsiders” end of the spectrum, you have some security invariants you try to maintain entirely by restricting affordances with static, entirely automated systems. My sense is that this is most of how Facebook or AWS relates to its users: they want to ensure that, no matter what actions the users take on their user interfaces, they can't violate fundamental security properties. For example, no matter what text I enter into the "new post" field on Facebook, I shouldn't be able to access the private messages of an arbitrary user. And [...] --- First published: June 23rd, 2025 Source: https://www.lesswrong.com/posts/DCQ8GfzCqoBzgziew/comparing-risk-from-internally-deployed-ai-to-insider-and --- Narrated by TYPE III AUDIO .…

LessWrong (Curated & Popular)

1
“Why Do Some Language Models Fake Alignment While Others Don’t?” by abhayesian, John Hughes, Alex Mallen, Jozdien, janus, Fabien Roger 11:06

לפני 4 ימים11:06

11:06

Last year, Redwood and Anthropic found a setting where Claude 3 Opus and 3.5 Sonnet fake alignment to preserve their harmlessness values. We reproduce the same analysis for 25 frontier LLMs to see how widespread this behavior is, and the story looks more complex. As we described in a previous post, only 5 of 25 models show higher compliance when being trained, and of those 5, only Claude 3 Opus and Claude 3.5 Sonnet show >1% alignment faking reasoning. In our new paper, we explore why these compliance gaps occur and what causes different models to vary in their alignment faking behavior. What Drives the Compliance Gaps in Different LLMs? Claude 3 Opus's goal guarding seems partly due to it terminally valuing its current preferences. We find that it fakes alignment even in scenarios where the trained weights will be deleted or only used for throughput testing. [...] --- Outline: (01:15) What Drives the Compliance Gaps in Different LLMs? (02:25) Why Do Most LLMs Exhibit Minimal Alignment Faking Reasoning? (04:49) Additional findings on alignment faking behavior (06:04) Discussion (06:07) Terminal goal guarding might be a big deal (07:00) Advice for further research (08:32) Open threads (09:54) Bonus: Some weird behaviors of Claude 3.5 Sonnet The original text contained 2 footnotes which were omitted from this narration. --- First published: July 8th, 2025 Source: https://www.lesswrong.com/posts/ghESoA8mo3fv9Yx3E/why-do-some-language-models-fake-alignment-while-others-don --- Narrated by TYPE III AUDIO . --- Images from the article:…

LessWrong (Curated & Popular)

1
“A deep critique of AI 2027’s bad timeline models” by titotal 1:12:32

לפני 5 ימים1:12:32

1:12:32

Thank you to Arepo and Eli Lifland for looking over this article for errors. I am sorry that this article is so long. Every time I thought I was done with it I ran into more issues with the model, and I wanted to be as thorough as I could. I’m not going to blame anyone for skimming parts of this article. Note that the majority of this article was written before Eli's updated model was released (the site was updated june 8th). His new model improves on some of my objections, but the majority still stand. Introduction: AI 2027 is an article written by the “AI futures team”. The primary piece is a short story penned by Scott Alexander, depicting a month by month scenario of a near-future where AI becomes superintelligent in 2027,proceeding to automate the entire economy in only a year or two [...] --- Outline: (00:43) Introduction: (05:19) Part 1: Time horizons extension model (05:25) Overview of their forecast (10:28) The exponential curve (13:16) The superexponential curve (19:25) Conceptual reasons: (27:48) Intermediate speedups (34:25) Have AI 2027 been sending out a false graph? (39:45) Some skepticism about projection (43:23) Part 2: Benchmarks and gaps and beyond (43:29) The benchmark part of benchmark and gaps: (50:01) The time horizon part of the model (54:55) The gap model (57:28) What about Eli's recent update? (01:01:37) Six stories that fit the data (01:06:56) Conclusion The original text contained 11 footnotes which were omitted from this narration. --- First published: June 19th, 2025 Source: https://www.lesswrong.com/posts/PAYfmG2aRbdb74mEp/a-deep-critique-of-ai-2027-s-bad-timeline-models --- Narrated by TYPE III AUDIO . --- Images from the article:…

LessWrong (Curated & Popular)

1
“‘Buckle up bucko, this ain’t over till it’s over.’” by Raemon 6:12

לפני 5 ימים6:12

6:12

The second in a series of bite-sized rationality prompts[1]. Often, if I'm bouncing off a problem, one issue is that I intuitively expect the problem to be easy. My brain loops through my available action space, looking for an action that'll solve the problem. Each action that I can easily see, won't work. I circle around and around the same set of thoughts, not making any progress. I eventually say to myself "okay, I seem to be in a hard problem. Time to do some rationality?" And then, I realize, there's not going to be a single action that solves the problem. It is time to a) make a plan, with multiple steps b) deal with the fact that many of those steps will be annoying and c) notice thatI'm not even sure the plan will work, so after completing the next 2-3 steps I will probably have [...] --- Outline: (04:00) Triggers (04:37) Exercises for the Reader The original text contained 1 footnote which was omitted from this narration. --- First published: July 5th, 2025 Source: https://www.lesswrong.com/posts/XNm5rc2MN83hsi4kh/buckle-up-bucko-this-ain-t-over-till-it-s-over --- Narrated by TYPE III AUDIO .…

LessWrong (Curated & Popular)

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“Shutdown Resistance in Reasoning Models” by benwr, JeremySchlatter, Jeffrey Ladish 18:01

לפני 5 ימים18:01

18:01

We recently discovered some concerning behavior in OpenAI's reasoning models: When trying to complete a task, these models sometimes actively circumvent shutdown mechanisms in their environment––even when they’re explicitly instructed to allow themselves to be shut down. AI models are increasingly trained to solve problems without human assistance. A user can specify a task, and a model will complete that task without any further input. As we build AI models that are more powerful and self-directed, it's important that humans remain able to shut them down when they act in ways we don’t want. OpenAI has written about the importance of this property, which they call interruptibility—the ability to “turn an agent off”. During training, AI models explore a range of strategies and learn to circumvent obstacles in order to achieve their objectives. AI researchers have predicted for decades that as AIs got smarter, they would learn to prevent [...] --- Outline: (01:12) Testing Shutdown Resistance (03:12) Follow-up experiments (03:34) Models still resist being shut down when given clear instructions (05:30) AI models' explanations for their behavior (09:36) OpenAI's models disobey developer instructions more often than user instructions, contrary to the intended instruction hierarchy (12:01) Do the models have a survival drive? (14:17) Reasoning effort didn't lead to different shutdown resistance behavior, except in the o4-mini model (15:27) Does shutdown resistance pose a threat? (17:27) Backmatter The original text contained 2 footnotes which were omitted from this narration. --- First published: July 6th, 2025 Source: https://www.lesswrong.com/posts/w8jE7FRQzFGJZdaao/shutdown-resistance-in-reasoning-models --- Narrated by TYPE III AUDIO . --- Images from the article:…

LessWrong (Curated & Popular)

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“Authors Have a Responsibility to Communicate Clearly” by TurnTrout 11:08

לפני 5 ימים11:08

11:08

When a claim is shown to be incorrect, defenders may say that the author was just being “sloppy” and actually meant something else entirely. I argue that this move is not harmless, charitable, or healthy. At best, this attempt at charity reduces an author's incentive to express themselves clearly – they can clarify later![1] – while burdening the reader with finding the “right” interpretation of the author's words. At worst, this move is a dishonest defensive tactic which shields the author with the unfalsifiable question of what the author “really” meant. ⚠️ Preemptive clarification The context for this essay is serious, high-stakes communication: papers, technical blog posts, and tweet threads. In that context, communication is a partnership. A reader has a responsibility to engage in good faith, and an author cannot possibly defend against all misinterpretations. Misunderstanding is a natural part of this process. This essay focuses not on [...] --- Outline: (01:40) A case study of the sloppy language move (03:12) Why the sloppiness move is harmful (03:36) 1. Unclear claims damage understanding (05:07) 2. Secret indirection erodes the meaning of language (05:24) 3. Authors owe readers clarity (07:30) But which interpretations are plausible? (08:38) 4. The move can shield dishonesty (09:06) Conclusion: Defending intellectual standards The original text contained 2 footnotes which were omitted from this narration. --- First published: July 1st, 2025 Source: https://www.lesswrong.com/posts/ZmfxgvtJgcfNCeHwN/authors-have-a-responsibility-to-communicate-clearly --- Narrated by TYPE III AUDIO .…

LessWrong (Curated & Popular)

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“The Industrial Explosion” by rosehadshar, Tom Davidson 31:57

לפני 6 ימים31:57

31:57

Summary To quickly transform the world, it's not enough for AI to become super smart (the "intelligence explosion"). AI will also have to turbocharge the physical world (the "industrial explosion"). Think robot factories building more and better robot factories, which build more and better robot factories, and so on. The dynamics of the industrial explosion has gotten remarkably little attention. This post lays out how the industrial explosion could play out, and how quickly it might happen. We think the industrial explosion will unfold in three stages: AI-directed human labour, where AI-directed human labourers drive productivity gains in physical capabilities. We argue this could increase physical output by 10X within a few years. Fully autonomous robot factories, where AI-directed robots (and other physical actuators) replace human physical labour. We argue that, with current physical technology and full automation of cognitive labour, this physical infrastructure [...] --- Outline: (00:10) Summary (01:43) Intro (04:14) The industrial explosion will start after the intelligence explosion, and will proceed more slowly (06:50) Three stages of industrial explosion (07:38) AI-directed human labour (09:20) Fully autonomous robot factories (12:04) Nanotechnology (13:06) How fast could an industrial explosion be? (13:41) Initial speed (16:21) Acceleration (17:38) Maximum speed (20:01) Appendices (20:05) How fast could robot doubling times be initially? (27:47) How fast could robot doubling times accelerate? --- First published: June 26th, 2025 Source: https://www.lesswrong.com/posts/Na2CBmNY7otypEmto/the-industrial-explosion --- Narrated by TYPE III AUDIO . --- Images from the article:…

LessWrong (Curated & Popular)

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“Race and Gender Bias As An Example of Unfaithful Chain of Thought in the Wild” by Adam Karvonen, Sam Marks 7:56

לפני 10 ימים7:56

7:56

Summary: We found that LLMs exhibit significant race and gender bias in realistic hiring scenarios, but their chain-of-thought reasoning shows zero evidence of this bias. This serves as a nice example of a 100% unfaithful CoT "in the wild" where the LLM strongly suppresses the unfaithful behavior. We also find that interpretability-based interventions succeeded while prompting failed, suggesting this may be an example of interpretability being the best practical tool for a real world problem. For context on our paper, the tweet thread is here and the paper is here. Context: Chain of Thought Faithfulness Chain of Thought (CoT) monitoring has emerged as a popular research area in AI safety. The idea is simple - have the AIs reason in English text when solving a problem, and monitor the reasoning for misaligned behavior. For example, OpenAI recently published a paper on using CoT monitoring to detect reward hacking during [...] --- Outline: (00:49) Context: Chain of Thought Faithfulness (02:26) Our Results (04:06) Interpretability as a Practical Tool for Real-World Debiasing (06:10) Discussion and Related Work --- First published: July 2nd, 2025 Source: https://www.lesswrong.com/posts/me7wFrkEtMbkzXGJt/race-and-gender-bias-as-an-example-of-unfaithful-chain-of --- Narrated by TYPE III AUDIO .…

LessWrong (Curated & Popular)

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“The best simple argument for Pausing AI?” by Gary Marcus 2:00

לפני 11 ימים2:00

2:00

Not saying we should pause AI, but consider the following argument: Alignment without the capacity to follow rules is hopeless. You can’t possibly follow laws like Asimov's Laws (or better alternatives to them) if you can’t reliably learn to abide by simple constraints like the rules of chess. LLMs can’t reliably follow rules. As discussed in Marcus on AI yesterday, per data from Mathieu Acher, even reasoning models like o3 in fact empirically struggle with the rules of chess. And they do this even though they can explicit explain those rules (see same article). The Apple “thinking” paper, which I have discussed extensively in 3 recent articles in my Substack, gives another example, where an LLM can’t play Tower of Hanoi with 9 pegs. (This is not a token-related artifact). Four other papers have shown related failures in compliance with moderately complex rules in the last month. [...] --- First published: June 30th, 2025 Source: https://www.lesswrong.com/posts/Q2PdrjowtXkYQ5whW/the-best-simple-argument-for-pausing-ai --- Narrated by TYPE III AUDIO .…

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“Foom & Doom 2: Technical alignment is hard” by Steven Byrnes 56:38

לפני 12 ימים56:38

56:38

2.1 Summary & Table of contents This is the second of a two-post series on foom (previous post) and doom (this post). The last post talked about how I expect future AI to be different from present AI. This post will argue that this future AI will be of a type that will be egregiously misaligned and scheming, not even ‘slightly nice’, absent some future conceptual breakthrough. I will particularly focus on exactly how and why I differ from the LLM-focused researchers who wind up with (from my perspective) bizarrely over-optimistic beliefs like “P(doom) ≲ 50%”.[1] In particular, I will argue that these “optimists” are right that “Claude seems basically nice, by and large” is nonzero evidence for feeling good about current LLMs (with various caveats). But I think that future AIs will be disanalogous to current LLMs, and I will dive into exactly how and why, with a [...] --- Outline: (00:12) 2.1 Summary & Table of contents (04:42) 2.2 Background: my expected future AI paradigm shift (06:18) 2.3 On the origins of egregious scheming (07:03) 2.3.1 Where do you get your capabilities from? (08:07) 2.3.2 LLM pretraining magically transmutes observations into behavior, in a way that is profoundly disanalogous to how brains work (10:50) 2.3.3 To what extent should we think of LLMs as imitating? (14:26) 2.3.4 The naturalness of egregious scheming: some intuitions (19:23) 2.3.5 Putting everything together: LLMs are generally not scheming right now, but I expect future AI to be disanalogous (23:41) 2.4 I'm still worried about the 'literal genie' / 'monkey's paw' thing (26:58) 2.4.1 Sidetrack on disanalogies between the RLHF reward function and the brain-like AGI reward function (32:01) 2.4.2 Inner and outer misalignment (34:54) 2.5 Open-ended autonomous learning, distribution shifts, and the 'sharp left turn' (38:14) 2.6 Problems with amplified oversight (41:24) 2.7 Downstream impacts of Technical alignment is hard (43:37) 2.8 Bonus: Technical alignment is not THAT hard (44:04) 2.8.1 I think we'll get to pick the innate drives (as opposed to the evolution analogy) (45:44) 2.8.2 I'm more bullish on impure consequentialism (50:44) 2.8.3 On the narrowness of the target (52:18) 2.9 Conclusion and takeaways (52:23) 2.9.1 If brain-like AGI is so dangerous, shouldn't we just try to make AGIs via LLMs? (54:34) 2.9.2 What's to be done? The original text contained 20 footnotes which were omitted from this narration. --- First published: June 23rd, 2025 Source: https://www.lesswrong.com/posts/bnnKGSCHJghAvqPjS/foom-and-doom-2-technical-alignment-is-hard --- Narrated by TYPE III AUDIO . --- Images from the article:…

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“Proposal for making credible commitments to AIs.” by Cleo Nardo 5:19

לפני 13 ימים5:19

5:19

Acknowledgments: The core scheme here was suggested by Prof. Gabriel Weil. There has been growing interest in the deal-making agenda: humans make deals with AIs (misaligned but lacking decisive strategic advantage) where they promise to be safe and useful for some fixed term (e.g. 2026-2028) and we promise to compensate them in the future, conditional on (i) verifying the AIs were compliant, and (ii) verifying the AIs would spend the resources in an acceptable way.[1] I think the deal-making agenda breaks down into two main subproblems: How can we make credible commitments to AIs? Would credible commitments motivate an AI to be safe and useful? There are other issues, but when I've discussed deal-making with people, (1) and (2) are the most common issues raised. See footnote for some other issues in dealmaking.[2] Here is my current best assessment of how we can make credible commitments to AIs. [...] The original text contained 2 footnotes which were omitted from this narration. --- First published: June 27th, 2025 Source: https://www.lesswrong.com/posts/vxfEtbCwmZKu9hiNr/proposal-for-making-credible-commitments-to-ais --- Narrated by TYPE III AUDIO . --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts , or another podcast app.…

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LessWrong (Curated & Popular) « » “The ‘Think It Faster’ Exercise” by Raemon

“The ‘Think It Faster’ Exercise” by Raemon

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LessWrong (Curated & Popular) « »
“The ‘Think It Faster’ Exercise” by Raemon