This fall Boaz Barak taught Harvard's first AI safety course (course website). Boaz has done an excellent job organizing and promoting the material; you may have seen his original post on LW. I was the head TA for the course, and helped Boaz run the course (alongside Natalie Abreu, Sunny Qin, and Hanlin Zhang). I wanted to give an inside look into the course and share a lot more of our material in order to help future iterations of the course go well, both at Harvard and similar courses at other universities.

I think this course was a good thing which more universities should do. If you are in a position to try to get a similar course running at your university, this post is for you, and aims to walk you through course logistics and course decisions. Feel invited to reach out with questions or comments. The syllabus is public, and all of the lectures are shared on youtube here.

This course was structured as a research seminar where students learned to replicate important AI safety papers and produce novel research. You can see their projects here.

Basic organization in bullet form:

• Assignments:
  • We [...]

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Outline:

(03:00) Assignment Structure

(07:46) General reflections

(10:21) Recommendations for future iterations:

(11:55) Aggregated Student Perspectives on the Course

(12:59) Overall Experience

(14:12) How the Course Influenced Students' Future Plans

(14:18) Shifts in Perspective

(14:57) Future Intentions

(15:39) Student Critiques

(17:22) Conclusion

(17:43) Wrap-up: Summary of all the resources we make public:

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First published:

Source:

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Narrated by TYPE III AUDIO.

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