Big Data's "theory-free" analysis is a statistical malpractice

One of the premises of Big Data is that it can be "theory free": rather than starting with a hypothesis ("men at buffets eat more when women are present," "more people will click this button if I move it here," etc) and then gathering data to validate your guess, you just gather a ton of data and look for patterns in it. Read the rest

Cataloging the problems facing AI researchers is a cross between a parenting manual and a management book

Concrete Problems in AI Safety, an excellent, eminently readable paper from a group of Google AI researchers and some colleagues, sets out five hard problems facing the field: robots might damage their environments to attain their goals; robots might figure out how to cheat to attain their goals; supervising robots all the time is inefficient; robots that are allowed to try novel strategies might cause disasters; and robots that are good at one task might inappropriately try to apply that expertise to another unrelated task. Read the rest