jxzhangjhu/intro_to_ml_safety

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	Not started
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	Not started	Ethan Gutierrez
Trojans	Not started	Ethan Gutierrez
Detecting Emergent Behavior	Not started
Honest Models	Not started
Intrasystem Goals or Power Aversion	Not started
Machine Ethics	Not started
ML for Improved Decision-Making	Not started
ML for Cyberdefense	Not started
Cooperative AI	Not started
X-Risk	Not started
Possible Existential Hazards	Not started
Safety-Capabilities Balance	Not started
Review and Conclusion	Not started