LessWrong (Curated & Popular)

When reading comments, you see is what other people think before reading the comment. As shown in an RCT, that information anchors your opinion, reducing your ability to form your own opinion and making the site's karma rankings less related to the comment's true value. I think the problem is fixable and float some ideas for consideration.

The LessWrong interface prioritizes social information

You read a comment. What information is presented, and in what order?

The order of information:

Who wrote the comment (in bold);
How much other people like this comment (as shown by the karma indicator);
How much other people agree with this comment (as shown by the agreement score);
The actual content.
This is unwise design for a website which emphasizes truth-seeking. You don't have a chance to read the comment and form your own opinion first. However, you can opt in to hiding usernames (until moused over) via your account settings page.

A 2013 RCT supports the upvote-anchoring concern

From Social Influence Bias: A Randomized Experiment (Muchnik et al., 2013):[1]

We therefore designed and analyzed a large-scale randomized experiment on a social news aggregation Web site to investigate whether knowledge of such aggregates [...]

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Outline:

(00:30) The LessWrong interface prioritizes social information

[... 6 more sections]

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First published:

April 27th, 2026


Source:

https://www.lesswrong.com/posts/YSsp9x8qrBucLoiWT/lesswrong-shows-you-social-signals-before-the-comment

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Narrated by TYPE III AUDIO.

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Images from the article:

In October, I wrote a post arguing that donating to Alex Bores's campaign for Congress was among the most cost-effective opportunities that I'd ever encountered.

(A bit of context: Bores is a state legislator in New York who championed the RAISE Act, which was signed into law last December.[1] He's now running for Congress in New York's 12th Congressional district, which runs from about 17th Street to 100th Street in Manhattan. If elected to Congress, I think he'd be a strong champion for AI safety legislation, with a focus on catastrophic and existential risk.)

It's been six months since then, and the election is just two months away (June 23rd), so I thought I'd revisit that post and give an update on my view of how things are going.




How is Alex Bores doing?

When I wrote my post, I expected Bores to talk little about AI during the campaign, just because it wasn't a high-salience issue to voters. But that changed in November, when Leading the Future (the AI accelerationist super PAC) declared Bores their #1 target. Since then, they've spend about $2.5 million on attack ads against him.

LTF's theory of change isn't actually to [...]

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Outline:

(00:54) How is Alex Bores doing?

(04:02) How to help

(06:02) A quick note about other opportunities

The original text contained 9 footnotes which were omitted from this narration.

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First published:

April 27th, 2026


Source:

https://www.lesswrong.com/posts/pjSKdcBjfvjGexr6A/update-on-the-alex-bores-campaign

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Narrated by TYPE III AUDIO.

In criminal law, the prosecution and the defense each try to establish a timeline — what happened, where, when, who was involved — and thereby determine whether the defendant is actually guilty of a crime.[1]

Community misconduct disputes are nothing like this.

There is only rarely disagreement over facts, and even when there is, it is not the crux of the matter. Community disputes are not for litigating facts. What they are for[2] is litigating three things:

The character of the accused
The character of the accuser
The importance of the accusation, in light of points 1 & 2
I think basically all the terrible things that happen in community disputes are a result of this.

When what's being ruled on is a person — their place in their community, their continued access to resources, their worth as a human being — the situation feels all-or-nothing, and often escalates out of control.

This dynamic:

discourages people from speaking out about their experiences, both because they may be reluctant to ‘ruin the person's life’ over something non-catastrophic, and because they know that they will be opening themselves up to a punishing level of scrutiny and criticism, and may [...]
The original text contained 2 footnotes which were omitted from this narration.

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First published:

April 22nd, 2026


Source:

https://www.lesswrong.com/posts/cekDpXqjugt5Q3JnC/community-misconduct-disputes-are-not-about-facts

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Narrated by TYPE III AUDIO.

Around 10 years ago, a paper came out that arguably killed classical deep learning theory: Zhang et al. 's aptly titled Understanding deep learning requires rethinking generalization.

Of course, this is a bit of an exaggeration. No single paper ever kills a field of research on its own, and deep learning theory was not exactly the most productive and healthy field at the time this was published. But if I had to point to a single paper that shattered the feeling of optimism at the time, it would be Zhang et al. 2016.[1]

Caption: believe it or not, this unassuming table rocked the field of deep learning theory back in 2016, despite probably involving fewer computational resources than what Claude 4.7 Opus consumed when I clicked the “Claude” button embedded into the LessWrong editor.

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Let's start by answering a question: what, exactly, do I mean by deep learning theory?

At least in 2016, the answer was: “extending statistical learning theory to deep neural networks trained with SGD, in order to derive generalization bounds that would explain their behavior in practice”.

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Since its conception in the mid 1980s, statistical learning theory had been the dominant approach for [...]

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

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First published:

April 25th, 2026


Source:

https://www.lesswrong.com/posts/ZvQfcLbcNHYqmvWyo/the-paper-that-killed-deep-learning-theory

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Narrated by TYPE III AUDIO.

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Images from the article:

Summary

EA and rationalists got enamoured with forecasting and prediction markets and made them part of the culture, but this hasn’t proven very useful, yet it continues to receive substantial EA funding. We should cut it off.

My Experience with Forecasting

For a while, I was the number one forecaster on Manifold. This lasted for about a year until I stopped just over 2 years ago. To this day, despite quitting, I’m still #8 on the platform. Additionally, I have done well on real-money prediction markets (Polymarket), earning mid-5 figures and winning a few AI bets. I say this to suggest that I would gain status from forecasting being seen as useful, but I think, to the contrary, that the EA community should stop funding it.

I’ve written a few comments throughout the years that I didn’t think forecasting was worth funding. You can see some of these here and here. Finally, I have gotten around to making this full post.

Solution Seeking a Problem

When talking about forecasting, people often ask questions like “How can we leverage forecasting into better decisions?” This is the wrong way to go about solving problems. You solve problems by starting with [...]

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First published:

April 25th, 2026


Source:

https://www.lesswrong.com/posts/WCutvyr9rr3cpF6hx/forecasting-is-way-overrated-and-we-should-stop-funding-it

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Narrated by TYPE III AUDIO.