I.B.M.’s Watson, Like a Good Designer, Thinks in Possibilities
After studying concept design for a while, I’ve come to the conclusion that the single best thing designers can do to come up with better concepts is to do more of them. Generating more options increases the chances we’ll find better ideas.
With that in mind, I perked up while reading What Is I.B.M.’s Watson?, part of the NY Times’s series on artificial intelligence, which incorporates a similar process as great designers I’ve seen…
Watson’s speed allows it to try thousands of ways of simultaneously tackling a “Jeopardy!” clue. Most question-answering systems rely on a handful of algorithms, but Ferrucci decided this was why those systems do not work very well: no single algorithm can simulate the human ability to parse language and facts. Instead, Watson uses more than a hundred algorithms at the same time to analyze a question in different ways, generating hundreds of possible solutions. Another set of algorithms ranks these answers according to plausibility; for example, if dozens of algorithms working in different directions all arrive at the same answer, it’s more likely to be the right one. In essence, Watson thinks in probabilities. It produces not one single “right” answer, but an enormous number of possibilities, then ranks them by assessing how likely each one is to answer the question.