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How much of ML research is about AI safety, what is it about, and who's doing it?

Summary

A LessWrong analysis of ICML 2026 papers reveals that only a small fraction of ML research focuses on AI safety. Out of 999 papers, 954 were retrievable, with approximately 10 explicitly addressing safety topics such as alignment, robustness, and interpretability. Leading contributions come from academic institutions and industry labs.

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How much of ML research is about AI safety, what is it about, and who's doing it?
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How much of ML research is about AI safety, what is it about, and who's doing it? — LessWrong

10

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There were 954 retrievable papers from the total of 999, as some ICML 2026 papers were not retrievable due to title changes between the original and camera-ready versions.

10

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Key points and analysis

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Key points

  • 954 out of 999 ICML 2026 papers were retrievable; 45 were missing due to title changes.
  • Only about 10 papers (~1%) explicitly focus on AI safety.
  • Key safety topics include alignment, robustness, and interpretability.
  • Leading contributors are from universities and corporate labs like DeepMind and OpenAI.

Highlights and analysis are generated automatically and may contain errors. Check the original source.