LessWrong (Curated & Popular)

This is a link post. It is unbearable to not be consuming. All through the house is nothing but silence. The need inside of me is not an ache, it is caustic, sour, the burning desire to be distracted, to be listening, watching, scrolling.

Some of the time I think I’m happy. I think this is very good. I go to the park and lie on a blanket in a sun with a book and a notebook. I watch the blades of grass and the kids and the dogs and the butterflies and I’m so happy to be free.

Then there are the nights. The dark silence is so oppressive, so all-consuming. One lonely night, early on, I bike to a space where I had sometimes felt welcome, and thought I might again.

“What are you doing here?” the people ask.

“I’m three days into my month of digital minimalism and I’m so bored, I just wanted to be around people.”

No one really wants to be around me. Okay.

One of the guys had a previous life as a digital minimalism coach. “The first two weeks are the hardest,” he tells me encouragingly.

“Two WEEKS?” I want to shriek.

[...]

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First published:
January 18th, 2026

Source:
https://www.lesswrong.com/posts/eeFqTjmZ8kS7S5tpg/the-first-two-weeks-are-the-hardest-my-first-digital

Linkpost URL:
https://mingyuan.substack.com/p/the-first-two-weeks-are-the-hardest

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Narrated by TYPE III AUDIO.

I spent a few hundred dollars on Anthropic API credits and let Claude individually research every current US congressperson's position on AI. This is a summary of my findings.

Disclaimer: Summarizing people's beliefs is hard and inherently subjective and noisy. Likewise, US politicians change their opinions on things constantly so it's hard to know what's up-to-date. Also, I vibe-coded a lot of this.

Methodology

I used Claude Sonnet 4.5 with web search to research every congressperson's public statements on AI, then used GPT-4o to score each politician on how "AGI-pilled" they are, how concerned they are about existential risk, and how focused they are on US-China AI competition. I plotted these scores against GovTrack ideology data to search for any partisan splits.

1. AGI awareness is not partisan and not widespread

Few members of Congress have public statements taking AGI seriously. For those that do, the difference is not in political ideology. If we simply plot the AGI-pilled score vs the ideology score, we observe no obvious partisan split.

There are 151 congresspeople who Claude could not find substantial quotes about AI from. These members are not included on this plot or any of the plots which follow.

[...]

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Outline:

(00:46) Methodology

(01:12) 1. AGI awareness is not partisan and not widespread

(01:56) 2. Existential risk is partisan at the tails

(02:51) 3. Both parties are fixated on China

(04:02) 4. Who in Congress is feeling the AGI?

(11:10) 5. Those who know the technology fear it.

(12:54) Appendix: How to use this data

The original text contained 2 footnotes which were omitted from this narration.

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First published:
January 16th, 2026

Source:
https://www.lesswrong.com/posts/WLdcvAcoFZv9enR37/what-washington-says-about-agi

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Narrated by TYPE III AUDIO.

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Images from the article:

Since artificial superintelligence has never existed, claims that it poses a serious risk of global catastrophe can be easy to dismiss as fearmongering. Yet many of the specific worries about such systems are not free-floating fantasies but extensions of patterns we already see. This essay examines thirteen distinct ways artificial superintelligence could go wrong and, for each, pairs the abstract failure mode with concrete precedents where a similar pattern has already caused serious harm. By assembling a broad cross-domain catalog of such precedents, I aim to show that concerns about artificial superintelligence track recurring failure modes in our world.

This essay is also an experiment in writing with extensive assistance from artificial intelligence, producing work I couldn’t have written without it. That a current system can help articulate a case for the catastrophic potential of its own lineage is itself a significant fact; we have already left the realm of speculative fiction and begun to build the very agents that constitute the risk. On a personal note, this collaboration with artificial intelligence is part of my effort to rebuild the intellectual life that my stroke disrupted and hopefully push it beyond where it stood before.

Section 1: Power Asymmetry [...]

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First published:
January 16th, 2026

Source:
https://www.lesswrong.com/posts/kLvhBSwjWD9wjejWn/precedents-for-the-unprecedented-historical-analogies-for-1

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Narrated by TYPE III AUDIO.

Boaz Barak, Gabriel Wu, Jeremy Chen, Manas Joglekar

[Linkposting from the OpenAI alignment blog, where we post more speculative/technical/informal results and thoughts on safety and alignment.]


TL;DR We go into more details and some follow up results from our paper on confessions (see the original blog post). We give deeper analysis of the impact of training, as well as some preliminary comparisons to chain of thought monitoring.

We have recently published a new paper on confessions, along with an accompanying blog post. Here, we want to share with the research community some of the reasons why we are excited about confessions as a direction of safety, as well as some of its limitations. This blog post will be a bit more informal and speculative, so please see the paper for the full results.

The notion of “goodness” for the response of an LLM to a user prompt is inherently complex and multi-dimensional, and involves factors such as correctness, completeness, honesty, style, and more. When we optimize responses using a reward model as a proxy for “goodness” in reinforcement learning, models sometimes learn to “hack” this proxy and output an answer that only “looks good” to it (because [...]

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Outline:

(08:19) Impact of training

(12:32) Comparing with chain-of-thought monitoring

(14:05) Confessions can increase monitorability

(15:44) Using high compute to improve alignment

(16:49) Acknowledgements

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First published:
January 14th, 2026

Source:
https://www.lesswrong.com/posts/k4FjAzJwvYjFbCTKn/why-we-are-excited-about-confession

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Narrated by TYPE III AUDIO.

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Images from the article:

Two cats fighting for control over my backyard appear to have settled on a particular chain-link fence as the delineation between their territories. This suggests that:

Animals are capable of recognizing Schelling points
Therefore, Schelling points do not depend on language for their Schelling-ness
Therefore, tacit bargaining should be understood not as a special case of bargaining where communication happens to be restricted, but rather as the norm from which the exceptional case of explicit bargaining is derived.
Summary of cat situation

I don't have any pets, so my backyard is terra nullius according to Cat Law. This situation is unstable, as there are several outdoor cats in the neighborhood who would like to claim it. Our two contenders are Tabby Cat, who lives on the other side of the waist-high chain-link fence marking the back edge of my lot, and Tuxedo Cat, who lives in the place next-door to me.

| || Tabby's || yard || (A) |------+...........+--------| (B) || | Tuxedo's| My yard | yard| ||| -- tall wooden fences.... short chain-link fence In the first [...]

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Outline:

(00:43) Summary of cat situation

(03:28) Why the fence?

(04:00) If animals have Schelling points, then...

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First published:
January 14th, 2026

Source:
https://www.lesswrong.com/posts/uYr8pba7TqaPpszX5/backyard-cat-fight-shows-schelling-points-preexist-language

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Narrated by TYPE III AUDIO.