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23 - Mechanistic Anomaly Detection with Mark Xu

23 - Mechanistic Anomaly Detection with Mark Xu

AXRP - the AI X-risk Research Podcast · Daniel Filan

July 27, 20232h 5m

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Show Notes

Is there some way we can detect bad behaviour in our AI system without having to know exactly what it looks like? In this episode, I speak with Mark Xu about mechanistic anomaly detection: a research direction based on the idea of detecting strange things happening in neural networks, in the hope that that will alert us of potential treacherous turns. We both talk about the core problems of relating these mechanistic anomalies to bad behaviour, as well as the paper "Formalizing the presumption of independence", which formulates the problem of formalizing heuristic mathematical reasoning, in the hope that this will let us mathematically define "mechanistic anomalies".

Patreon: patreon.com/axrpodcast

Ko-fi: ko-fi.com/axrpodcast

Episode art by Hamish Doodles: hamishdoodles.com/

Topics we discuss, and timestamps:

- 0:00:38 - Mechanistic anomaly detection

- 0:09:28 - Are all bad things mechanistic anomalies, and vice versa?

- 0:18:12 - Are responses to novel situations mechanistic anomalies?

- 0:39:19 - Formalizing "for the normal reason, for any reason"

- 1:05:22 - How useful is mechanistic anomaly detection?

- 1:12:38 - Formalizing the Presumption of Independence

- 1:20:05 - Heuristic arguments in physics

- 1:27:48 - Difficult domains for heuristic arguments

- 1:33:37 - Why not maximum entropy?

- 1:44:39 - Adversarial robustness for heuristic arguments

- 1:54:05 - Other approaches to defining mechanisms

- 1:57:20 - The research plan: progress and next steps

- 2:04:13 - Following ARC's research

The transcript: axrp.net/episode/2023/07/24/episode-23-mechanistic-anomaly-detection-mark-xu.html

ARC links:

- Website: alignment.org

- Theory blog: alignment.org/blog

- Hiring page: alignment.org/hiring

Research we discuss:

- Formalizing the presumption of independence: arxiv.org/abs/2211.06738

- Eliciting Latent Knowledge (aka ELK): alignmentforum.org/posts/qHCDysDnvhteW7kRd/arc-s-first-technical-report-eliciting-latent-knowledge

- Mechanistic Anomaly Detection and ELK: alignmentforum.org/posts/vwt3wKXWaCvqZyF74/mechanistic-anomaly-detection-and-elk

- Can we efficiently explain model behaviours? alignmentforum.org/posts/dQvxMZkfgqGitWdkb/can-we-efficiently-explain-model-behaviors

- Can we efficiently distinguish different mechanisms? alignmentforum.org/posts/JLyWP2Y9LAruR2gi9/can-we-efficiently-distinguish-different-mechanisms