The robots who predict the long run

When you ask Benjamin Recht, creator of , he’d likely let you know our current predicament has lots to do with the concept and beliefs of decision theory—or what economists call rational alternative theory. Recht, a polymathic professor in UC Berkeley’s Department of Electrical Engineering and Computer Science, prefers the term “mathematical rationality” to explain the narrow, statistical conception that stoked the need to construct computers, informed how they’d eventually work, and influenced the sorts of problems they’d be good at solving. 

This belief system goes all the best way back to the Enlightenment, but in Recht’s telling, it truly took hold on 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 within the fight against the Axis powers convinced a select group of scientists and statisticians that they may also be a logical basis for designing the primary computers. Thus was born the concept of a pc as a super rational agent, a machine capable of constructing 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 era drive the automated decisions of our modern world, whether or not it’s in managing supply chains, scheduling flight times, or placing advertisements in your social media feeds,” he writes. On this optimization-­driven reality, “every life decision is posed as if it were a round at an imaginary casino, and each argument could be reduced to costs and advantages, 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 individuals who fundamentally imagine the world could be a greater place if more of us adopted their analytic mindset and learned to weigh costs and advantages, estimate risks, and plan optimally. In other words, these are individuals who imagine we must always all make decisions like computers. 

How might we exhibit that (unquantifiable) human intuition, morality, and judgment are higher ways of addressing a number of the world’s most vital and vexing problems?

It’s a ridiculous idea for multiple reasons, he says. To call only 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 within 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 latest theories of thermodynamics, quantum mechanics, and relativity.” We also managed to construct cars and airplanes and not using a formal system of rationality and one way or the other got here up with societal innovations like modern democracy without optimal decision theory. 

So how might we persuade the Pinkers and Silvers of the world that almost all decisions we face in life aren’t actually grist for the unrelenting mill of mathematical rationality? Furthermore, how might we exhibit that (unquantifiable) human intuition, morality, and judgment is likely to be higher ways of addressing a number of the world’s most vital and vexing problems?

DOUBLEDAY, 2026

One might start by reminding the rationalists that any prediction, computational or otherwise, is basically only a —but one with a strong tendency to self-fulfill. This concept animates Carissa Véliz’s splendidly wide-ranging polemic . 

A philosopher on 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 powerful enough, the prediction becomes the reason behind its becoming true.”