This simple spreadsheet of machine learning foibles may not look like much but it’s a fascinating exploration of how machines “think.” The list, compiled by researcher Victoria Krakovna, describes various situations in which robots followed the spirit and the letter of the law at the same time.
For example, in the video below a machine learning algorithm learned that it could rack up points not by taking part in a boat race but by flipping around in a circle to get points. In another simulation “where survival required energy but giving birth had no energy cost, one species evolved a sedentary lifestyle that consisted mostly of mating in order to produce new children which could be eaten (or used as mates to produce more edible children).” This led to what Krakovna called “indolent cannibals.”
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