Matt Salganik (@msalganik) and I are looking for a joint postdoc at Princeton to explore the fundamental limits of machine learning for prediction. We welcome quantitatively minded candidates from many fields including computer science and social science. [Thread]
This is an unusual position. Here's how it came to be. Last year I gave a talk on AI snake oil. Meanwhile Matt led a mass collaboration that showed the limits of machine learning for predicting kids’ life outcomes. Paper in PNAS: pnas.org/content/117/15…
https://twitter.com/random_walker/status/1196870349574623232
We realized we were coming at the same fundamental question from different angles: given enough data and powerful algorithms, is everything predictable? So we teamed up and taught a course on limits to prediction. We're excited to share the course pre-read cs.princeton.edu/~arvindn/teach…
During the course, we read papers on prediction from a dozen domains ranging from computer vision to civil wars. We developed a basic understanding of the limits to prediction in different domains and for different problems. We hope to share a synthesis soon.
But there’s much more that we can’t answer yet. Join us and help us figure it out! Our Center at Princeton is also hiring postdocs to work on many other tech policy topics. We’ll start reviewing applications soon. Apply here: citp.princeton.edu/programs/fello…
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