Summary
I'm increasingly convinced that model access parity is a big deal and we are not on track to achieve it. By model access parity, I mean a small gap between (i) the model access for lab employees and (ii) the model access for external safety researchers, third-party auditors, and other actors trying to make the future go well). See here for an introduction.
The basic case is this: (1) Regardless of the strategic landscape, outsiders are well-suited to many crucial activities. (2) Outsiders will be positioned to spend billions of dollars towards making things go well.[1] (3) AI labour seems like the most promising route for spending money to tackle these activities. However, during the months where outsider activities are highest leverage, the best internal models might provide 2 to 60 times more uplift than the best publicly-available models.[1] So without model access parity, this AI labour might be massively less effective.
In this post, I attempt to sketch some interventions. But I don't think any of them are great, mostly because they don't seem sticky. I wouldn't be surprised if you can think of something much better.
My overall judgement
Outsider orgs should try to directly advocate [...]
---
Outline:
(00:12) Summary
(01:24) My overall judgement
(03:13) List of interventions
(03:56) Workarounds if we lose model access parity
The original text contained 2 footnotes which were omitted from this narration.
---
First published:
July 2nd, 2026
---
Narrated by TYPE III AUDIO.
Fler avsnitt av LessWrong (30+ Karma)
Visa alla avsnitt av LessWrong (30+ Karma)LessWrong (30+ Karma) med LessWrong finns tillgänglig på flera plattformar. Informationen på denna sida kommer från offentliga podd-flöden.
