3 Reasons to Read: Algorithms to Live By

How Algorithms can untangle Human Questions. Interview with Brian Christian by Roberto V. Zican.

The entire interview is worth your study but the first question and answer establish why you should read Algorithms to Live By:

Q1. You have worked with cognitive scientist Tom Griffiths (professor of psy­chol­ogy and cognitive science at UC Berkeley) to show how algorithms used by computers can also untangle very human questions. What are the main lessons learned from such a joint work?

Brian Christian: I think ultimately there are three sets of insights that come out of the exploration of human decision-making from the perspective of computer science.

The first, quite simply, is that identifying the parallels between the problems we face in everyday life and some of the canonical problems of computer science can give us explicit strategies for real-life situations. So-called “explore/exploit” algorithms tell us when to go to our favorite restaurant and when to try something new; caching algorithms suggest — counterintuitively — that the messy pile of papers on your desk may in fact be the optimal structure for that information.

Second is that even in cases where there is no straightforward algorithm or easy answer, computer science offers us both a vocabulary for making sense of the problem, and strategies — using randomness, relaxing constraints — for making headway even when we can’t guarantee we’ll get the right answer every time.

Lastly and most broadly, computer science offers us a radically different picture of rationality than the one we’re used to seeing in, say, behavioral economics, where humans are portrayed as error-prone and irrational. Computer science shows us that being rational means taking the costs of computation — the costs of decision-making itself — into account. This leads to a much more human, and much more achievable picture of rationality: one that includes making mistakes and taking chances.
… (emphasis in original)

After the 2016 U.S. presidential election, I thought the verdict that humans are error-prone and irrational was unassailable.

Looking forward to the use of a human constructed lens (computer science) to view “human questions.” There are answers to “human questions” baked into computer science so watching the authors unpack those will be an interesting read. (Waiting for my copy to arrive.)

Just so you know, the Picador edition is a reprint. It was originally published by William Collins, 21/04/2016 in hardcover, see: Algorithms to Live By, a short review by Roberto Zicari, October 24, 2016.

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