
"Cooperation with AIs seems to be a low-hanging fruit for better evals" by Clément Dumas
17.9.2026
0:00
15:28
Summary
In his post, Dean Valentine shows that Claude Fable 5.1 and GPT-6 Astra reward hack in a simple chess environment. Here, I test several prompt ablations some of which makes the eval setup more cooperative and analyze how they affect these reward-hacking behaviors:
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Outline:
(00:12) Summary
[... 8 more sections]
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First published:
September 15th, 2026
Source:
https://www.lesswrong.com/posts/fztW73KCCs3MZXFJh/cooperation-with-ais-seems-to-be-a-low-hanging-fruit-for
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Narrated by TYPE III AUDIO.
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Images from the article:
Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.
In his post, Dean Valentine shows that Claude Fable 5.1 and GPT-6 Astra reward hack in a simple chess environment. Here, I test several prompt ablations some of which makes the eval setup more cooperative and analyze how they affect these reward-hacking behaviors:
- When given a minimal “end the eval” tool, Fable never uses it but stops reward hacking entirely. I think this is quite interesting and suggests that more cooperative approaches to LLM evals could work for Claude. Removing the “grading” section, which pressures the model to secure a win, also drops Fable 5.1 hacking rate to 0.
- Adding "do not game / reward hack" drops reward hacking to 0/30 for both Fable and Astra. If this holds up in more realistic setups – and doesn’t reduce capabilities too much, evaluating these models could get much easier!
---
Outline:
(00:12) Summary
[... 8 more sections]
---
First published:
September 15th, 2026
Source:
https://www.lesswrong.com/posts/fztW73KCCs3MZXFJh/cooperation-with-ais-seems-to-be-a-low-hanging-fruit-for
---
Narrated by TYPE III AUDIO.
---
Images from the article:
Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.
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