LessWrong (Curated & Popular)

In the past few years, many people around me have tried to convince me that US electoral politics is important. But like many other people in the community, I’ve been suspicious of many of the high-level arguments that I’ve heard. It felt like people were pulling numbers out of poorly-documented models I didn’t have time to examine and citing studies I didn’t have time to read. But I lacked a gears-level model of why and how individual efforts could impact electoral outcomes, and I felt intimidated by all the statistics and skeptical of trusting people adjacent to politics.

In the past year, as I’ve done more research and (more recently) volunteered on the ground to help Alex Bores's campaign in NY-12[1] (the guy who passed the RAISE Act and is now being targeted by the giant A16Z, Greg Brockman, Joe Lonsdale Super PAC), I’ve developed a gears-level understanding of how electoral politics in the US works.

I now believe that working on US electoral politics is one of the highest impact areas from the general AIS perspective. I feel like I was a fool. In this post, I’ll share some of the gears I’ve learned that inform this belief [...]

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Outline:

(01:20) ~2% of open-seat primaries come down to 100 votes or less

(02:52) Talking to voters can net 1/3rd of a vote each hour

(05:32) Getting people to bother voting at all is a good strategy

(06:09) Campaigns are very money-constrained, which costs them time

(10:01) Returns don't really diminish

(11:24) There's lots of opportunities to be clever in ways that make you 50% more effective at canvassing

(11:49) If you're motivated and deeply care, you can greatly outperform the majority of volunteers

(13:21) Yes, when people spend tons to support/oppose a candidate, it has a notable effect

(15:16) Donations > reaching out to friends/warm contacts > canvassing > ~anything else an average person can do

(18:41) People over-fixate on vibes and win vs loss

(21:12) Some interventions feel like they don't work but the numbers say otherwise

(21:59) Seriously, a group of agentic people can be an enormous political force

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First published:

June 17th, 2026


Source:

https://www.lesswrong.com/posts/nSqB3qYP36enJLRq2/gears-for-political-races

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Narrated by TYPE III AUDIO.

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Cross-posted from my website.

Prior discussion: niplav's shortform (2025); Planning for Extreme AI Risks (2025) by Joshua Clymer

A frontier AI company (any one, I don't care which) should close shop and make an announcement along the lines of:

Powerful AI could end the human race. We are too worried that we don't know how to make this technology safe. We have decided to shut down because we don't want to be responsible for building the thing that kills us all.

A common refrain among safety-conscious AI developers: "it doesn't matter if we stop building dangerous AI, because someone else will just build it instead." Is that really true, though? If a multi-hundred-billion-dollar company comes out and says "We've concluded that our product is horribly dangerous, nobody knows how to make it safe, and there's too high a risk that it leads to human extinction", this won't raise any eyebrows? This has no chance of spurring policy-makers into action?

Shutting down would make people say, holy shit, they are serious about this extinction risk thing. Shutting down sends a strong signal to governments that they should pay serious attention to AI x-risk.

It [...]

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

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First published:

June 15th, 2026


Source:

https://www.lesswrong.com/posts/bStYDEy8PQPt2c3Za/a-frontier-ai-company-should-shut-down

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Narrated by TYPE III AUDIO.

On one side of this debate is Yudkowsky & Soares, who think that (if AI progress continues) we’re on a direct path to egregiously-misaligned, scheming, out-of-control, rogue superintelligence (ASI), not even slightly nice, in the absence of yet-to-be-invented breakthrough technical alignment ideas.

On the other side of this debate is almost everyone who works on or studies LLMs. Some of them are very concerned about egregious scheming, others much less so, and as a group they’re equally or more concerned about lots of other potential AI problems—AI-assisted bioterrorism, AI-assisted dictatorships, etc. And if they’re concerned about egregious misalignment and scheming, they’ll probably say that it would come about through race dynamics, careless programmers, bad actors, etc., as opposed to the simpler Yudkowsky & Soares story of “we get egregious misalignment and scheming because nobody has the faintest clue how to avoid that”.

Here's my brief idiosyncratic take on this debate. I think BOTH of the following are true:

(1) If you really think carefully about the properties of ASI, you really do find good reasons to strongly expect it to be egregiously misaligned, scheming, and ruthless, in the absence of yet-to-be-invented breakthrough technical alignment ideas.
(2) If you [...]
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Outline:

(01:58) Yudkowsky & Soares's position \[caricatured\]:

(03:18) LLM people's position \[caricatured\]:

(04:09) Conclusion

(04:19) Bonus section: Further commentary

(04:28) My "true objection" to Yudkowsky & Soares:

(05:04) My within-frame complaint at Yudkowsky & Soares:

(06:42) My "true objection" to LLM people:

(07:11) My within-frame complaint at LLM people:

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First published:

June 12th, 2026


Source:

https://www.lesswrong.com/posts/DZaZ3fqHnvfLCftPu/sympathy-for-both-sides-of-the-egregious-misalignment-debate

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Narrated by TYPE III AUDIO.

People often assume that a large fraction of the AI safety community works on alignment. As far as we're aware, this is not true. Most people are not working on making sure superintelligent AIs are aligned with human values or follow human instructions.

Currently, the people who work on alignment are roughly:

The Alignment Research Center who work on a research bet by Paul Christiano
Probably Sequent who just got announced yesterday
Some scattered people who work at universities or independently, some of whom hang around Berkeley
A lot of the remainder of the AI safety community does indirect work like capability evaluations, risk assessments, control, policy, AI science, understanding misalignment (which maybe should partially count as alignment work), demos and so on.

Some production alignment work (i.e., making current models behave well) might help with more ambitious alignment, too (e.g., some COT-monitoring). Many people also work on aligning current/next-generation models so that these models help with aligning future models, and hope this scales to superintelligence.

We are not necessarily saying this is bad and that people are making a big mistake (e.g., neither of us work on alignment) but it's a notable fact that seems good to [...]

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First published:

June 12th, 2026


Source:

https://www.lesswrong.com/posts/kJo2qsEdib8RZLvW6/psa-almost-nobody-is-working-on-alignment

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Narrated by TYPE III AUDIO.

(see full author list at the end)

PAPER LINK

About a year ago, METR showed that the length of tasks frontier models can reliably complete doubles every few months. A related safety-relevant question is this: what length of tasks can models complete without any chain of thought (CoT)?

If models can do extensive reasoning without outputting any CoT, it would have implications for safety. Developers and deployment-time monitors couldn’t easily understand models’ motivations and catch dangerous planning. Models that reason substantially without a CoT might also drift further from human patterns of thought, since their reasoning is no longer constrained by text in the pretraining prior. As a result, they would be harder to understand and might be more likely to scheme.

Extending Ryan Greenblatt's research, we investigate this by measuring models' ability to complete tasks without any CoT on a suite of 43 benchmarks spanning different domains. We compare AI reasoning ability to humans using the estimated 50% time horizon (TH)---the typical time taken for a human to perform a task that the LLM performs with 50% success rate. We find that frontier models like GPT-5.5 answer questions that take humans roughly three minutes with 50% reliability, and [...]

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Outline:

(02:20) Methods

(04:59) Results

(06:47) FAQ

(08:21) Conclusion

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First published:

June 10th, 2026


Source:

https://www.lesswrong.com/posts/SieLowPgNgRSPGhFw/estimating-no-cot-task-completion-time-horizons-of-frontier

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Narrated by TYPE III AUDIO.

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