The Irrational Decision: How We Gave Computers the Power to Choose for Us - Hardcover

by Benjamin Recht (Author)

How the computer revolution shaped our conception of rationality--and why human problems require solutions rooted in human intuition, morality, and judgment

In the 1940s, mathematicians set out to design computers that could act as ideal rational agents in the face of uncertainty. The Irrational Decision tells the story of how they settled on a peculiar mathematical definition of rationality in which every decision is a statistical question of risk. Benjamin Recht traces how this quantitative standard came to define our understanding of rationality, looking at the history of optimization, game theory, statistical testing, and machine learning. He explains why, now more than ever, we need to resist efforts by powerful tech interests to drive public policy and essentially rule our lives.

While mathematical rationality has proven valuable in accelerating computers, regulating pharmaceuticals, and deploying electronic commerce, it fails to solve messy human problems and has given rise to a view of a rational world that is not only overquantified but surprisingly limited. Recht shows how these mathematical methods emerged from wartime research and influenced fields ranging from economics to health care, drawing on illuminating examples ranging from diet planning to chess to self-driving cars.

Highlighting both the power and limitations of mathematical rationality, The Irrational Decision reveals why only humans can resolve fundamentally political or value-based questions and proposes a more expansive approach to decision making that is appropriately supported by computational tools yet firmly rooted in human intuition, morality, and judgment.

Author Biography

Benjamin Recht is professor of electrical engineering and computer sciences at the University of California, Berkeley. He is the author (with Stephen J. Wright) of Optimization for Data Analysis and (with Moritz Hardt) Patterns, Predictions, and Actions: Foundations of Machine Learning (Princeton).