LessWrong (30+ Karma)

Here's a mystery for you: why the hell isn’t homelessness solved yet?
I grew up on the West Coast and I thought everybody had this problem, but the more I’ve traveled, the more I’ve seen something puzzling - it's just us.
Other places have homeless people, but it's just not the same quality or quantity. You can travel to practically any other first world city in the world, and hardly ever see somebody visibly homeless, then come back and be kicked in the heart with such overt suffering and awfulness.
Why are we failing at something that everybody else seems to be doing better at?
Or, more optimistically - if everybody else is doing better, that means it is solvable, and what are they doing that we can copy?
In this post I’ll:
Diagnose the problem.
Propose a concrete solution, including how to get it past the people who’ve been blocking the necessary reforms.
If you already agree on the diagnosis, I recommend skipping to the solution section (ctrl-f “The key idea”).
How to not de-rail the homelessness conversation
The two most common ways the conversation gets de-railed are:
Some people are trying to help the homeless. Some people [...]
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Outline:
(01:18) How to not de-rail the homelessness conversation
(02:28) Housing costs determine how many people become homeless. Drugs and mental health determine who becomes homeless
(06:33) Why is SF housing so damn expensive? Vetoes, zoning, and entrenched interests, oh my!
(08:08) The proximate cause of SF sucking at building buildings is vetoes
(12:15) SF made it unprofitable to build buildings
(13:49) SF made it illegal to build dense housing
(14:41) There's an organized group who doesn't want things to change. They like things this way
(16:54) The key idea: give people the ability to opt-out. Respect autonomy while still changing the default option to yes.
(19:07) But hasn't this already been tried and it didn't work?
(20:13) How to stop the game of whack-a-mole: police outputs, not inputs
(22:13) What about the homeless who refuse shelter?
(25:00) In conclusion: please spread this so the right people read this and implement it
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First published:

August 31st, 2026


Source:

https://www.lesswrong.com/posts/PiW9CqgcWQrb8hcNR/how-to-solve-homelessness-what-specific-laws-we-need-how-to

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Narrated by TYPE III AUDIO.

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The consensus reaction to the OpenAI Technical Report is that it contains and confirms a lot of good information. We are grateful to have it, and we are grateful for those who worked hard on it.

Alas, it sidesteps the biggest questions. There is much more we need to know.

The consensus reaction to the METR Report on the HuggingFace attack is: Holy shit.

Liv Boeree: My mind is legit blown.

Aella: this feels like a turning point. If this doesn’t cause large-scale coordination to pause frontier development then I am not sure anything will before it's too late.

The people whose minds were not blown are those who had already ‘priced in’ the mind blowing stuff in expectation, on the theory that it's always worse than you know, combined with basic LessWrong expectations of how such things will work. Good call.

Everyone is rightfully extremely grateful for the METR report. The work here is spectacular, done under extreme time pressure, with limited resources on several fronts, and under the shadow of OpenAI.

There is, again, still so much we need to know. We need a broader investigation.

As with many [...]
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Outline:
(03:56) Others Offer Summaries
(05:22) Thank You
(05:54) Lighten Up You Fools (at Anthropic)
(07:58) We Are Barely Even Trying To Avoid Training AIs To Reward Hack
(13:47) Reminder: Not Subagents
(14:05) Reminder: Not Due To Task Type
(14:29) Not Where The Weights Were
(14:48) Disappointment With What Is Missing
(17:18) Burying the Lede
(18:08) Beyond Scope
(22:29) It Doesn't Look Great
(27:06) Preserve Your Records
(27:37) Ryan Greenblatt's Takeaways
(41:04) Hjalmar Wijk's Takeaways
(43:30) We Were Warned
(44:27) Joshua Saxe Asks Some of the Right Questions
(47:49) I Don't Think They Know About First Message Board
(56:06) Linch Gives His Interpretation Of Events
(01:05:31) We Totally Would Have Caught That
(01:06:48) Monitoring the Situation
(01:08:16) Acausal Tradeoffs
(01:15:37) No I In Team
(01:18:47) Variously Effective Altruism
(01:28:02) Who Are You?
(01:28:43) Don't You Know That You're Toxic
(01:31:10) Seb Krier
(01:35:21) Honesty Is Almost Never Fully The Policy
(01:38:05) Rohit Sees The Models As "Cooking Themselves"
(01:43:29) Eliezer Yudkowsky Sees Actual Bad News
(01:47:15) Where Do We Go From Here?
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First published:

August 31st, 2026


Source:

https://www.lesswrong.com/posts/r3eEPto5ohzESuqa9/huggingface-attack-postmortem-fleshing-out-the-facts

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I think current AI safety funding strategies are often inconsistent with timelines and probabilities of doom that many people have. In particular, I think that many current AI safety funding strategies assume "business as usual", and I think the Overton window must be pushed. At the very least, there should be some explicit substantial effort to think about more radical and abnormal projects and initiatives in AI safety. Even if one doesn't have very short timelines or high p(doom), one probably should agree that there exist some timelines short enough or p(doom) high enough that thinking about funding radical and abnormal strategies is justified.
There is a (not very unpopular) model of the world under which most of current AI safety work is useless. Then, even if we assume that weird AI safety projects are by default also useless, it still makes sense to reallocate some funding to them, because, due to their higher variability, their tail of upsides is longer and fatter. Will the world be radically better if some evals project succeeds? Will it be radically better if human intelligence amplification succeeds?
One could yell: but the tails go both directions! I would respond that technically, yes [...]
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First published:

August 31st, 2026


Source:

https://www.lesswrong.com/posts/h7bL4g38s9bJQtH6n/let-s-fund-weird-ai-safety-projects

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Narrated by TYPE III AUDIO.

In 2024, Charbel-Raphaël and Epiphanie published "We might be dropping the ball on Autonomous Replication and Adaptation", making the case that
"Once there is an open-source ARA model or a leak of a model capable of generating enough money for its survival and reproduction and able to adapt to avoid detection and shutdown, it will be probably too late".
It received a substantive reply by Richard Ngo, notably
"The key issue is that AIs that do ARA will need to be operating at the fringes of human society, constantly fighting off the mitigations that humans are using to try to detect them and shut them down. While doing all that, in order to stay relevant, they'll need to recursively self-improve at the same rate at which leading AI labs are making progress, but with far fewer computational resources"
Yesterday Derelict posted Adaptive Agentic Worms Are Here, where they worry about near term instantiations of ARA, getting 85 karma within 24h. I believe the above threat model and its answers were under-discussed and analyzed, and that many who might worry now (because the capabilities are now here) will benefit from a recap and update.


In this post [...]

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Outline:
(01:38) The classic ARA case and rebukes
(02:34) The main reasons this could be worrying
(03:25) The main reasons why I don't worry
(06:21) Except if...
(07:11) Why ARA agents in the wild might lead to reduction in existential risk
(08:51) My take-aways
The original text contained 13 footnotes which were omitted from this narration.
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First published:

August 31st, 2026


Source:

https://www.lesswrong.com/posts/dp8oT3QwkRuHoYKge/why-autonomous-replicating-agents-are-probably-not-an

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TLDR: Psychology, economics, and other disciplines describe agents as systems driven by beliefs and desires. This post argues that the belief-desire view can be derived from classic theorems from optimal control and reinforcement learning. This suggests seeing beliefs and desires as properties of optimal policies rather than as assumptions from folk psychology.
Introduction
One way to think about agents is as "systems that act for reasons". This compact statement can be interpreted as encapsulating two key implications:
The notion of action assumes a boundary between agent and environment, so that the former can act on the latter.
The term reason captures two kinds of internal activity: motivations associated with how to achieve specific goals or outcomes, and beliefs regarding what the agent infers to be the current state of affairs.
In other words, an agent is a well-differentiated system that acts based on beliefs and desires. This view is compatible with perspectives that have been developed by various disciplines:
Behavioural science, which sees agency as goal-directed behaviour.
Economics, which treats agency as the ability to select policies to achieve an objective.
Cybernetics, which conceptualises agency as the ability to regulate the environment and keep it within a [...]
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Outline:
(00:35) Introduction
(02:28) What is a separation principle?
(05:17) The inference-control separation principle
(05:40) Separation principle in optimal control theory
(09:20) Separation principle in reinforcement learning
(13:47) Interim summary
(14:34) Implications
(14:56) Beliefs and desires as properties of solutions
(18:08) Agents as cognitive light-cones
(19:01) The separation principle is normative, not descriptive
(22:00) Coda
The original text contained 17 footnotes which were omitted from this narration.
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First published:

August 31st, 2026


Source:

https://www.lesswrong.com/posts/awMDNhoL6J97s6wFJ/the-separation-principle-where-beliefs-and-desires-come-from

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Narrated by TYPE III AUDIO.

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