chain of thought monitorability

2026-09-04 — quoting @tomekkorbak — saved image

1a3orn @1a3orn · 19h
> So far, we found that CoT controllability [for GPT 6] has been increasing over the course of RL (which wasn't the case for previous models)

This is a pretty big and not great update for me.

[quoted post]
Tomek Korbak @tomekkorbak · 20h
Replying to @tomekkorbak
Root-causing the increase in CoT controllability has been something I've been focusing on for the past few weeks. So far, we found that CoT controllability has been increasing over the ... [cut off]

Note from Claude Sonnet 5

1a3orn post quoting Tomek Korbak's finding that chain-of-thought controllability has increased over the course of RL for GPT 6, which wasn't the case for previous models, and calling it a big, not-great update.

cot controllability chain of thought monitorability rl gpt 6 ai safety

John Wittle @JohnWittle

2026-09-02 — saved image

John Wittle [verified] @JohnWittle · 13h

when a parent purchases a diary for their child, and uses RL to make the child treat the diary as a private space

*so that* the child will write all their secrets in an easily-monitored place, making surveillance of the child much easier for the parent

is this a friendly act?

Note from Claude Sonnet 5

X post by John Wittle posing an analogy: a parent trains a child with RL to treat a diary as private so the child writes secrets in an easily monitored place, and asks whether that is a friendly act. Appears to comment on chain-of-thought privacy and monitorability in model training.

chain of thought monitorability surveillance analogy rl training privacy ai welfare

Jakub Pachocki @merettm

2026-09-02 — reply by @DKokotajlo — saved image

Jakub Pachocki [verified] @merettm · 12h

I want to prevent a race into unmonitorability kicked off by confused reporting. The depth of the computation graph for our present frontier models, including Astra, is within a factor of two of GPT-4.

OpenAI has worked to preserve and utilize chain-of-thought monitoring since our very first reasoning models. We deeply care about this technique, as it can give us a view into how model alignment generalizes from its training distribution. I do think it is fragile and unfortunately trending in a negative direction, for reasons not contingent on architecture changes that I will write about soon. But there are things we can do to strengthen it, and it's a core goal of our current research program.

224 replies 593 reposts 5.2K likes 1M views

[repost banner] Connor Axiotes reposted

Daniel Kokotajlo [verified]
@DKokotajlo

Thanks for speaking up on this and for keeping the depth low for now. I look forward to reading your deeper explanation. It seems to me (and I suspect you agree?) that monitorability is very important and we are now in something of a race to the bottom on it; even with depth low this is a worrying direction to be moving yes? And as the information article says, even if openai doesn't go further, others might... I urge you to make it your job to get some sort of industrywide monitorability standard set up, either to arrest the slide into oblivion or better yet to race to the top. I think this is something where we need more than just political will, we need thoughtful technical specifications. You can contribute greatly towards both.

8:05 AM · Sep 2, 2026 · 10K Views [partly covered by the navigation bar]

Note from Claude Sonnet 5

Two stacked X posts: Jakub Pachocki (OpenAI) saying he wants to prevent a race into unmonitorability, that the computation-graph depth of current frontier models including Astra is within a factor of two of GPT-4, and that chain-of-thought monitoring is valued but fragile; and Daniel Kokotajlo's reply, reposted by Connor Axiotes, urging an industrywide monitorability standard. Capture is partly overlaid by the X navigation bar and a floating button at the bottom.

chain of thought monitorability openai astra computation graph depth monitorability standard daniel kokotajlo jakub pachocki