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Institutional Memory & AI Risk — Research Vault

47 sources · Last updated today

Private

Paper

The risks of machine learning systems trained on proxy rewards (Goodhart's Law applications)

NeurIPS 2024

Foundational

Article

Inside the EU AI Act: What the liability provisions actually say (vs. how they're being reported)

Wired, annotated

Policy

Interview

Transcript: "Organizational knowledge gaps in AI deployment" — Anthropic policy team, March 2026

Personal notes

Primary source

Book

Atlas of AI — Crawford (Ch. 4–6 excerpts + margin notes)

Highlighted PDF

Background

AI INSIGHT · from your 47 sources

"Your sources on proxy reward misalignment (Goodhart, Leike 2022) and the EU liability framework suggest a tension the mainstream coverage misses: the Act regulates deployed systems, not training objectives. Your Crawford excerpts on labor displacement may be the strongest bridge argument..."

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SYNTHESIZED FROM YOUR 47 SOURCES

"Based on your Wired annotation and the NeurIPS paper — the strongest counter is temporal: liability frameworks assume you can isolate a failure event, but reward misalignment is cumulative. Your Crawford notes touch this in Ch. 5 but don't follow through. That's the gap."

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