Making data meaningless so AI can map its meaning

AI Outside In is a column by PAIR's writer-in-residence, David Weinberger, who offers his outsider perspective on key ideas in machine learning. His opinions are his own and do not necessarily reflect those of Google. Suppose you want a machine learning system to suggest paint names based on any color you specify. This has been done hilariously by Janelle Shane -- "burf pink," "navel tan" -- but let's say we want to do it more seriously (and without any reference to how Shane actually did it). Machine learning, at least of the common sort called "supervised learning", learns from the data you give it, so you first want to gather a large set of colors to which humans have applied various labels.