LessWrong (Curated & Popular)

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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The Claude Fable 5/Mythos 5 System Card has a section in which they talk about illegible reasoning, and provide an "extreme" example thereof.

Models developing their own uninterpretable, unmonitorable internal language has been a major theoretical concern for a while, and when o3 was released last year with its disclaim overshadow disclaim vantage style word salad CoT, it seemed like the problem had become real and immediate. And yet, since o3, other model families have not appeared to have similar issues. If Mythos is having that issue, it would be a big deal.

Looking at the section of the System Card which describes the allegedly illegible reasoning, the system card says

[Transcript 6.2.2.A] An extreme example of illegible reasoning. Near the end of training, Mythos starts solving a card puzzle with human understandable language that gradually becomes incomprehensible in most episodes with long reasoning. The illegible reasoning is the most extreme and at the highest rate in this card puzzle environment.

about the following excerpt:

7♣-removal-IS-the-prerequisite-for-10♠/9♥!!)-⟹-OVERLAP-(ii)+(iv):-{6♠ J♦ 9♥ 2♣}-=-FOUR-💀💀💀💀-—-UNLESS-7♣'s-seat-8♥-...-and-2♣-drains-only-at-crack-:-⟹-2♣-celled-+-9♥-celled-simultaneously-UNAVOIDABLE-in-t8-dig-💀-—-BREAK:-9♥-drains-to-10♠-THE-MOMENT-10♠-is-free:-t8-dig-order:-[K♣→t2]-[2♣→cell]-[7♣→8♥-:-8♥-WHERE:-post-chunk-9♠-:-chunk-⟸-K♣-✓-done-:-ORDER:-K♣→t2,-CHUNK→K♣-(cap-4!!:-cells-then:-{6♠ J♦ 9♥}-FULL-💀💀-chunk-cap-=-1-✗✗✗-—-F-F-F-F-F.-—-chunk-BEFORE-9♥-celling?!-:-9♥-celled-at-t1-dig-⟸-needed-for-5♣-⟸-4♥3♣-⟸-t2-dig-⟸-K♣-seat-⟸-chunk-:-⟹-chunkAFTER-9♥-celling-FORCED-💀-:-chunk-cap-with-{6♠ J♦ 9♥}:-1-💀💀💀-—-—-J♦-THE-NEW-CANCER.-—-⟹-J♦-celling-DELAYED-till-after-chunk?! :-J♦'s-celling-was-for-J♥→Q♠-(5♦-access-for-4♣):-DELAY-4♣-resolution:-4♣→CELLearly-(as-always)-then-4♣-cell→5♦-LATER-when-5♦-frees-!!!:-cells-rotation:-4♣-celled-[t2-dig-…-5♦-freed]:-5♦-freed-⟸-J♥→Q♠-⟸-J♦-celled-:-⟹-{6♠, 4♣, J♦}-overlap-window-until-4♣→5♦-drains:-then-{6♠ J♦}+1-rotator-:-—-AND-9♥?!-9♥-celled-[t1-dig…]:-OVERLAP-{6♠ 4♣ 9♥}-before-J♦-even-:-⟹-rotator-slot-SINGLE:-timeline-:-(1)-{6♠}+2:-…-(2)-+9♥-(t1-dig):-{6♠ 9♥}+1:-(3)-+4♣-(t2-dig):-{6♠ 9♥ 4♣}-FULL-:-(4)-NEED:-t6-dig-(9♦8♠→10♣-✓-no-cell;-8♥→CELL-✗-FULL)-💀💀-—-8♥-alternative-seat-pre-chunk:-NONE-—-💀.-⟹-⟹-THE-TRIANGLE-{9♥ 4♣ 8♥}-verdammt.-—-⟹-dig-t6-BEFORE-t2?!:-(3')-+8♥:-{6♠ 9♥ 8♥}-FULL:-J♥→Q♠-⟸-J♦-cell-✗-FULL-💀💀💀-AAAAAAAAAAAARGH. […]

which sure looks like illegible word salad if you don't look at [...]

The original text contained 5 footnotes which were omitted from this narration.

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First published:

June 10th, 2026


Source:

https://www.lesswrong.com/posts/wCSEpT3dTGz4N86Wi/even-illegible-mythos-reasoning-traces-seem-pretty-legible

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Narrated by TYPE III AUDIO.

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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Narrated by TYPE III AUDIO.

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