AI Alignment Theory Course: Readings and Rapporteur Reports!

As I announced on this blog a couple weeks ago, I’m teaching a new course this semester at UT Austin, entitled AI Alignment Theory. To call such a course “timely” seems like an understatement; this is the first course I’ve ever taught for which multiple gargantuan developments relevant to the course have happened while I was teaching it. Since AI alignment is still a field with no standard textbook (although that might be changing), no accepted body of mathematical theory, etc. etc., the way we’ve been running the course is like a humanities discussion seminar, albeit one that happens to be in a CS department and to include technical results from time to time. Basically, in each class session, a student “rapporteur” gives a talk on an AI alignment reading—which include “ancient” readings (from way back in 2016), “modern” readings (from, say, last week), and everything in between—and then we freely discuss and debate whatever was presented, with my own role mostly limited to that of…