You need to sign in or sign up before continuing.

A review by sifter
Prediction Machines: The Simple Economics of Artificial Intelligence by Joshua Gans, Avi Goldfarb, Ajay Agrawal

3.0

Written by the officer class of Davos, it’s a charmless and mostly self-satisfied read where the same people blurbing it on the jacket are quoted admiringly inside its pages.

BUT. It’s quick and the chapter summaries are very crisp and there the focus on AI = cheap, plentiful, accurate predictions *is* an interesting and useful frame for AI within business in the next 5 years.

There’s also some useful first principles stuff on prediction - “prediction requires a specificity not found in mission statements.” (An under-appreciated part of facebook’s success and why they are now coming unstuck is their leadership’s ability to be specific in what they want - sharing, likes, engagement etc)

“Companies often find themselves having to go back to basics to realign on their objectives and sharpen their mission statement as a first step in their AI strategy”

“prediction and judgement are complements so better prediction [AI] increases the demand for judgement, meaning that your employees’ main role will be to exercise judgement in decision making.”

Good summary on the final page of the trade offs for society around AI:

* Productivity vs (wealth/power) distribution
* Innovation vs competition
* Performance vs privacy