This is a low-effort post. I mostly want to get other people's takes and express concern about the lack of detailed and publicly available plans so far. This post reflects my personal opinion and not necessarily that of other members of Apollo Research. I’d like to thank Ryan Greenblatt, Bronson Schoen, Josh Clymer, Buck Shlegeris, Dan Braun, Mikita Balesni, Jérémy Scheurer, and Cody Rushing for comments and discussion.

I think short timelines, e.g. AIs that can replace a top researcher at an AGI lab without losses in capabilities by 2027, are plausible. Some people have posted ideas on what a reasonable plan to reduce AI risk for such timelines might look like (e.g. Sam Bowman's checklist, or Holden Karnofsky's list in his 2022 nearcast), but I find them insufficient for the magnitude of the stakes (to be clear, I don’t think these example lists were intended to be an [...]

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Outline:

(02:36) Short timelines are plausible

(07:10) What do we need to achieve at a minimum?

(10:50) Making conservative assumptions for safety progress

(12:33) So whats the plan?

(14:31) Layer 1

(15:41) Keep a paradigm with faithful and human-legible CoT

(18:15) Significantly better (CoT, action and white-box) monitoring

(21:19) Control (that doesn't assume human-legible CoT)

(24:16) Much deeper understanding of scheming

(26:43) Evals

(29:56) Security

(31:52) Layer 2

(32:02) Improved near-term alignment strategies

(34:06) Continued work on interpretability, scalable oversight, superalignment and co

(36:12) Reasoning transparency

(38:36) Safety first culture

(41:49) Known limitations and open questions

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Narrated by TYPE III AUDIO.