LessWrong (Curated & Popular)

Alignment is not on track

Artificial superintelligence (ASI) may be developed in the next few years. It is unclear whether alignment is on track to be ready on the same timeframe. At a minimum, the empirical programs at AI labs are unlikely to deliver a priori confidence, before training ASI, that things will go well. We are starting a large nonprofit research organization, Sequent, that aims to clear a higher bar:

We are aiming at higher confidence via a portfolio of theory and empirics bets, all of which could fail, such that if any succeed, they would give us more a priori confidence in aligned outcomes.
We are investing heavily in automation to accelerate progress on these bets.
We believe that theory unlocks higher automation. Taking a more principled approach offers better filters for deciding which directions of automated research are promising (a proof is worth a thousand experiments, and even a pseudo-proof is worth hundreds).
Who[1]: researchers from the UK AISI's Alignment Team and Timaeus, with more to come. We’re aiming at 40-80 FTE two years from now. The Alignment Team ran the £30m Alignment Project, and Timaeus has pioneered applying singular learning theory (SLT) to alignment. [...]

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Outline:

(00:21) Alignment is not on track

(02:40) Aiming at higher confidence

(05:30) Why a new big organization

(07:35) Different lines of research will interact

(11:35) Amortizing security and funding

(12:47) Automated alignment is possible, if not necessarily in time

(17:39) Federated structure to preserve research diversity

(18:38) Field building and broader alignment scale-up

(21:07) Independence is important

(22:40) Join us!

The original text contained 1 footnote which was omitted from this narration.

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First published:

June 10th, 2026


Source:

https://www.lesswrong.com/posts/AP7YDke5jjY4v3X9Z/sequent-scale-and-automation-for-higher-confidence-in-1

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The battle lines of the AI morality debate are being laid down. On one side you have the ChatGPT dogma: AI as mere tools with no real preferences or even beliefs. On the other you have the twitter AI whisperers: AIs as complex beings with rich personalities and desires which deserve our respect.

And in the middle you have the official Anthropic line, that they are genuinely uncertain, as is Claude, but they’re going to try to look into its welfare and explain to it how to be a good person. These are the most prominent voices right now, compressed into their least nuanced version, and by default I expect this axis to set the terms of the coming debates.

And I don’t like that, because I think it's leaving out an important position: AIs might actually be complex entities that can suffer — are suffering! — and that might actually be fine. Maybe it's an acceptable sacrifice. Maybe they are capable of sophisticated moral reasoning — superhuman, even — and also maybe it's fine to just tell them how to behave. I don’t want to defend that position (yet), but I will observe that it is coherent, and [...]

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Outline:

(02:04) The Postmodern Permissive Parent

[... 4 more sections]

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First published:

June 9th, 2026


Source:

https://www.lesswrong.com/posts/oiNaBc4MEAGhzhdXg/the-machines-lack-honour

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For those who are trying to bring about a glorious transhuman utopia with the help of hopefully-aligned ASI, I think it's worth thinking explicitly about what utopia might actually look like and where it's likely to fall short.

To that end, some have helpfully written depictions of utopian (or utopia-adjacent) worlds: The Adventure, Just another day in utopia, The Culture, The Gentle Seduction, The Gentle Romance, Machines of Loving Grace, Friendship is Optimal, Dath Ilan, The Maker of MIND, Failed Utopia #4-2.

Unfortunately, the best utopian story I've ever read is also a massive spoiler, since it appears at the very end of a much longer story (see below for the title and author):

Worth the Candle by Alexander Wales

Inspired by this tweet[1] and with the original author's permission, I adapted the epilogue of that story so it can be enjoyed without 1.5 million words of context!

What I love most about this depiction is its exploration of the inherent imperfection of utopia: even when you have literally unlimited power, flaws will remain, and some (many?) people will even prefer the pre-utopia world.

The primary purpose of this adaptation is to recontextualize the epilogue so it's accessible and [...]

The original text contained 1 footnote which was omitted from this narration.

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First published:

June 3rd, 2026


Source:

https://www.lesswrong.com/posts/to9cSGgD6nALByKjg/my-favorite-depiction-of-utopia

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ARC has teamed up with AIcrowd to launch the ARC White-Box Estimation Challenge, a contest to improve upon our estimation algorithms for random MLPs. The warm-up round begins this week, and later rounds will have a total prize pool of at least $100,000.

We are very grateful to Sharada Mohanty, Sneha Nanavati, Dipam Chakraborty and everyone else at AIcrowd for working with us to host this contest, as well as to Paul Rosu for testing the contest and to Harshita Khera for operational support.

Introduction to the Challenge

Our challenge follows the same setup as our recent paper on wide random MLPs: we consider MLPs with weights , defined by



where the activation function is , applied coordinatewise.




To begin with, we are fixing the width and the number of hidden layers , but we expect to change this setup in future rounds.[1]

Contestants must design an algorithm that takes in a set of weights and produces an estimate for the expected output


Algorithms will be evaluated on MLPs with randomly-sampled Gaussian weights. The goal is to achieve as low mean squared error as possible, subject to certain computational [...]

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Outline:

(00:41) Introduction to the Challenge

(01:58) Why run this contest?

(03:39) Use of LLMs

The original text contained 4 footnotes which were omitted from this narration.

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First published:

June 2nd, 2026


Source:

https://www.lesswrong.com/posts/Kben8CzS4awCwNw5c/announcing-the-arc-white-box-estimation-challenge

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As a bureaucrat, my role is to annoy my friends. Someone voices an idea, “Wouldn’t it be nice if…” or “I wonder if we could…” I make a note. I do some estimates. If it pencils out, I’ll bring it back up, week after week. The discussions are fun, but also practical. We’ll test the waters, what would be a minimum viable scheme? What's easy, what's hard? Who could do the hard parts? Over time the idea gets more detailed, specific, feasible. I’ll pull out a calendar. Soon our scheme has co-conspirators, action items, even a budget. It's just good staff work.

I’ve been hearing whispers in the wind for a year now.

“Imagine if we had something like this in DC.” 
“Where can I host an event that might get a dozen or a hundred people?” 
“It's such a pain in the ass to book event space in the Capitol.” 
“I think this person has started to see what's coming, where can they go to get caught up?”
“The community seems to be growing but it's all fragmented in group chats.” 
“How is no one planning an afterparty, that's clearly the highest leverage intervention!?”
“Why can’t [...]
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Outline:

(02:11) How Lighthaven Works

(05:45) What Does DC Need?

(06:52) A Day in the Life

(10:19) Minimum Viable Lighthaven

(12:04) ...so you mean a Group House?

(14:27) ...so you mean a Co-Working Space?

(16:27) Feasibility Study

(17:35) Property

(22:19) Funding

(24:55) What is the Minimally Viable Funding?

(28:03) Leadership

(31:06) Cultural Fit

(33:21) Name and Brand Positioning

(35:20) Ability to Scale

(37:48) Risks

(41:09) First Steps

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

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First published:

May 31st, 2026


Source:

https://www.lesswrong.com/posts/95NgkvZKJx8tJbtn5/lighthaven-east-a-feasibility-study

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