University of Oxford economist Max Kasy is pushing back hard on the popular notion that artificial intelligence is an unstoppable technological tidal wave and we're all on the beach waiting powerlessly for it to crash over us. That view of AI is wrong — or at least, conveniently incomplete, says Kasy, who runs the Machine Learning and Economics Group at Oxford and who’s just written a new book called The Means of Prediction: How AI Really Works (and Who Benefits). The title is a play on words referencing what Karl Marx and Friedrich Engels called the means of production—the industrial assets that gave their capitalist owners the power to define social classes according to their interests. Pull aside the curtain on AI development, Kasy says, and you see something similar: AI is just a tool—yes, a powerful one—but nonetheless one being shaped, as we speak, by specific choices made by specific people with specific interests. And understanding that, he says, is the first step toward doing something about it. He joins me today to talk about ways to give users and the public a say in AI’s development and deployment, why strategies like protecting individual data privacy are unlikely to help, and what things like transparency requirements, basic income, and job guarantees have to do with making AI work for everyone rather than just a handful of tech giants.

Maximilian Kasy is a professor of economics at the University of Oxford and coordinator of the Machine Learning and Economics Group in the Oxford Department of Economics. He is the author of the book The Means of Prediction: How AI Really Works (and Who Benefits). His research interests include machine learning theory, the social impact of algorithmic decision making, the political economy of AI, economic inequality, basic income and job guarantee programs, adaptive experimental design, and Statistical decision theory. He holds a Ph.D. in economics and an M.A. in statistics from the University of California at Berkeley and magister degrees in mathematics and economics from the University of Vienna. In addition to his teaching at Oxford, he has also been an assistant professor at Harvard and UCLA and a visiting professor at MIT. Among numerous other professional affiliations, he is a research fellow at the Centre for Economic Policy Research.

Economics for Inclusive Prosperity (EfIP) is a network of academic economists from Harvard, Princeton, Columbia, and other leading universities who are committed to an inclusive economy and society. EfIP members are working to transform their field around a new vision of prosperity—a vision that includes traditional economic metrics, but also expanded measures of wellbeing including access to health, to democratic participation, and to a livable planet. They’re also highlighting the important changes in economics that are already underway.

Host Ralph Ranalli is a podcaster, entrepreneur, and former journalist, who has also hosted “HKS PolicyCast,” the award-winning flagship podcast of the Harvard Kennedy School. He holds a BA in political science from UCLA and a master’s in journalism from Columbia University.

The Economics for Inclusive Prosperity Podcast is recorded at the Malcolm Wiener Center for Social Policy at the Kennedy School of Government at Harvard University. The show is co-produced by Ralph Ranalli and Tony Ditta.