When I meet someone who works in a field outside of computer science, I usually
ask them a lot of questions about their field that I'm curious about. (This is
still relevant even
Introduction
There has been much recent discussion about AI risk, meaning specifically the
potential pitfalls (both short-term and long-term) that AI with improved
capabilities could create for society. Discussants include AI researchers such
[Highlights for the busy: de-bunking standard "Bayes is optimal" arguments;
frequentist Solomonoff induction; and a description of the online learning
framework.]
Short summary. This essay makes many points, each of which I think
I've decided to branch out a bit from technical discussions and engage in, as
Scott Aaronson would call it, some metaphysical spouting
[http://www.scottaaronson.com/blog/?cat=12]. The topic of today
(This is available in pdf form here
[http://web.mit.edu/jsteinha/www/stats-essay.pdf].)
If you are a newly initiated student into the field of machine learning, it
won't be long before