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Intro to ML Safety course notes

This repository contains notes for the Intro to ML Safety course.

Currently, the notes are not yet complete. We are looking for volunteers who will help us finish them. Ideally, notes will present the information from lectures and readings in a different way, so that students can have multiple angles of looking at the same material. Notes shouldn't just be notes from the lectures and ideally will include citations to papers.

If you would like to contribute to the course notes, feel free to make a pull request! We will credit you here and in the course notes.

Some prelimary notes on some of the topics already exist, but they aren't complete.

Lecture Status Contributor(s)
Introduction Not started
Deep Learning Review Ready for Review Nathaniel Li
Risk Decomposition Ready for Review Cody Rushing
Accident Models Not started
Black Swans Not started
Adversarial Robustness Needs revision Oliver Zhang
Black Swan Robustness Needs revision Oliver Zhang
Anomaly Detection Needs revision Oliver Zhang
Interpretable Uncertainty Needs revision Oliver Zhang
Transparency Ready for Review Cody Rushing
Trojans Ready for Review Ethan Gutierrez
Detecting Emergent Behaviour Ready for Review Bilal Chughtai
Honest Models Not started
Intrasystem Goals or Power Aversion Not started
Machine Ethics Not started
ML for Improved Decision-Making Ready for Review Nathaniel Li
ML for Cyberdefense Not started
Cooperative AI Ready for Review Bilal Chughtai
X-Risk Not started
Possible Existential Hazards Not started
Safety-Capabilities Balance Not started
Review and Conclusion Not started

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