One of the benefits of producing this podcast at the University of Chicago is that there are often events on campus that bring in not just one Big Brain, but many in order to find answers to the some of the most complex problems of our time. I recently had the pleasure of hosting one such event on artificial intelligence that we want to share with you today. It was part of the Graham School’s Leadership & Society Initiative Symposium, examined how AI could change everything and, more importantly, whether it should.

Artificial intelligence is evolving faster than most of us can keep up with—and its impact is already reshaping our lives, from the hospital to the courtroom to the art studio. Is AI moving too fast? Are we focusing on the wrong questions? And what comes after today’s generation of models? It’s a candid, complex, and eye-opening conversation you won’t want to miss.

For a more than a century, the Food and Drug Administration has worked to protect public health. In his research, Harvard University physician-researcher Jerry Avorn has examined how the FDA’s once-rigorous gold standard approval process has been affected by a powerful shortcut known as the Accelerated Approval Program—originally designed for desperate AIDS and cancer patients. He says that change in the 1990s has allowed more than half of all new drugs onto the market before drug companies have proven they actually help people.

In his new book Rethinking Medications: Truth, Power and the Drugs We Take, Avorn cites numerous examples: from a cold medicine that doesn’t de-congest to billion-dollar cancer treatments that only shrink lab results to the controversial Alzheimer’s drug Aduhelm—approved despite no clear cognitive benefits. In this episode, Avorn explores whether some prescriptions in your medicine cabinet are safe, effective and worth the money.

Prof. James Evans, a University of Chicago sociologist and data scientist, believes we’re training AI to think too much like humans—and it’s holding science back.

In this episode, Evans shares how our current models risk narrowing scientific exploration rather than expanding it, and explains why he’s pushing for AIs that think differently from us—what he calls “cognitive aliens.” Could these “alien minds” help us unlock hidden breakthroughs? And what would it take to build them?