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TL;DR: We develop three agents that autonomously perform alignment auditing tasks. When tested against models with intentionally-inserted alignment issues, our agents successfully uncover an LLM's hidden goal, build behavioral evaluations, and surface concerning LLM behaviors. We are using these agents to assist with alignment audits of frontier models like Claude 4.
Read the full Anthropic Alignment Science blog post. The X thread and blog post introduction are reproduced below.
Thread
(Original here)
New Anthropic research: Building and evaluating alignment auditing agents.
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As AI systems become more powerful, we need scalable ways to assess their alignment.
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Our [...]
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Outline:
(00:45) Thread
(03:53) Introduction
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First published:
Source:
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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.
By LessWrongTL;DR: We develop three agents that autonomously perform alignment auditing tasks. When tested against models with intentionally-inserted alignment issues, our agents successfully uncover an LLM's hidden goal, build behavioral evaluations, and surface concerning LLM behaviors. We are using these agents to assist with alignment audits of frontier models like Claude 4.
Read the full Anthropic Alignment Science blog post. The X thread and blog post introduction are reproduced below.
Thread
(Original here)
New Anthropic research: Building and evaluating alignment auditing agents.
--
As AI systems become more powerful, we need scalable ways to assess their alignment.
--
Our [...]
---
Outline:
(00:45) Thread
(03:53) Introduction
---
First published:
Source:
---
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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