The robots who predict the future


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The Irrational Decision: How We Gave Computers the Power to Choose for Us
Benjamin Recht

PRINCETON UNIVERSITY PRESS, 2026

If you ask Benjamin Recht, author of The Irrational Decision: How We Gave Computers the Power to Choose for Us, he’d likely tell you our current predicament has a lot to do with the idea and ideology of decision theory—or what economists call rational choice theory. Recht, a polymathic professor in UC Berkeley’s Department of Electrical Engineering and Computer Science, prefers the term “mathematical rationality” to describe the narrow, statistical conception that stoked the desire to build computers, informed how they would eventually work, and influenced the kinds of problems they would be good at solving. 

This belief system goes all the way back to the Enlightenment, but in Recht’s telling, it truly took hold at the tail end of World War II. Nothing focuses the mind on risk and quick decision-making like war, and the mathematical models that proved especially useful in the fight against the Axis powers convinced a select group of scientists and statisticians that they might also be a logical basis for designing the first computers. Thus was born the idea of a computer as an ideal rational agent, a machine capable of making optimal decisions by quantifying uncertainty and maximizing utility.

Intuition, experience, and judgment gave way, says Recht, to optimization, game theory, and statistical prediction. “The core algorithms developed in this period drive the automated decisions of our modern world, whether it be in managing supply chains, scheduling flight times, or placing advertisements on your social media feeds,” he writes. In this optimization-­driven reality, “every life decision is posed as if it were a round at an imaginary casino, and every argument can be reduced to costs and benefits, means and ends.”

Today, mathematical rationality (wearing its human skin) is best represented by the likes of the pollster Nate Silver, the Harvard psychologist Steven Pinker, and an assortment of Silicon Valley oligarchs, says Recht. These are people who fundamentally believe the world would be a better place if more of us adopted their analytic mindset and learned to weigh costs and benefits, estimate risks, and plan optimally. In other words, these are people who believe we should all make decisions like computers. 

How might we demonstrate that (unquantifiable) human intuition, morality, and judgment are better ways of addressing some of the world’s most important and vexing problems?

It’s a ridiculous idea for multiple reasons, he says. To name just one, it’s not as if humans couldn’t make evidence-based decisions before automation. “Advances in clean water, antibiotics, and public health brought life expectancy from under 40 in the 1850s to 70 by 1950,” Recht writes. “From the late 1800s to the early 1900s, we had world-changing scientific breakthroughs in physics, including new theories of thermodynamics, quantum mechanics, and relativity.” We also managed to build cars and airplanes without a formal system of rationality and somehow came up with societal innovations like modern democracy without optimal decision theory. 

So how might we convince the Pinkers and Silvers of the world that most decisions we face in life are not in fact grist for the unrelenting mill of mathematical rationality? Moreover, how might we demonstrate that (unquantifiable) human intuition, morality, and judgment might be better ways of addressing some of the world’s most important and vexing problems?

cover of Prophecy
Prophecy: Prediction, Power, and the Fight for the Future, from Ancient Oracles to AI
Carissa Véliz

DOUBLEDAY, 2026

One might start by reminding the rationalists that any prediction, computational or otherwise, is really just a wish—but one with a powerful tendency to self-fulfill. This idea animates Carissa Véliz’s wonderfully wide-ranging polemic Prophecy: Prediction, Power, and the Fight for the Future, from Ancient Oracles to AI

A philosopher at the University of Oxford, Véliz sees a prediction as “a magnet that bends reality toward itself.” She writes, “When the force of the magnet is strong enough, the prediction becomes the cause of its becoming true.” 



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