How Algorithms Use Your Data to Control You
6/9/20261 hr 34 min
Michael Shermer speaks with Oxford philosopher Carissa Véliz about the long human desire to know the future—from ancient oracles and astrology to AI, surveillance capitalism, predictive policing, and "data-driven" decision-making. Véliz argues that prediction is rarely neutral: the same machinery that collects personal data also tries to forecast behavior, and once institutions start treating predictions as facts, forecasts can become tools of control.
The conversation gets into why privacy matters for democracy, how algorithms can turn human lives into self-fulfilling prophecies, and why extraordinary people often fall outside predictive models.
Shermer and Véliz also discuss the limits of science, the replication crisis, crime statistics, effective altruism, utilitarian ethics, and free will.
Carissa Véliz is an associate professor at the Institute for Ethics in AI at the University of Oxford. Her first book, Privacy Is Power (Melville House) was an Economist book of the year and has been published in seven languages. Her academic work has been published in The Harvard Business Review, Nature, AI & Society, and The American Journal of Bioethics, among others. Her new book is Prophecy: Prediction, Power, and the Fight for the Future, from Ancient Oracles to AI.
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Transcript preview
First 90 secondsCarissa Véliz· Guest0:00
Uncertainty is a good news because it means that the future is not written, and that you can intercede, and that it's partly up to you. If you knew exactly what you were going to do tomorrow, and a year from now, and 10 years from now, you'd probably be living in a police state.
Michael Shermer· Host0:13
What is your position on the nature of our privacy today?
Carissa Véliz· Guest0:16
It's not in a great state. We are increasing surveillance with all of this data collection, partly to feed machinery of prediction, and that's how these two topics go together because the machinery of surveillance is at the service of the machinery of prediction. That al- already tells you something. You wouldn't surveil if you didn't want to predict. And why do you wanna predict? Because you wanna control. What does it mean to control? To either influence people's behavior or to react to people's behavior. I think that there are some jobs that, sure, in theory could be done by AI, but we wouldn't want it to, and we wouldn't get the same, uh, from it. So teaching is a perfect example. There are so many studies that show that people don't learn as much from screens. You can learn something, but it's really when a human being teaches you that inspires you and that makes you learn. And when I think back on high school, I had an incredible teacher, a guy called, um, Roger Goweron, who taught me Latin and taught me Shakespeare, and this guy had read Shakespeare dozens of times, but every time he would cry reading Shakespeare, and it was that kind of emotion that got me interested as a teenager and got me to think, "Okay, there's something important happening there," that I would have never gotten from a screen.
Michael Shermer· Host1:20
[upbeat music] All right, everybody, it's Michael Shermer. It's time for another episode of The Michael Shermer Show, brought to you, as always, by the Skeptic Society