🎙️ Moran Cerf, Neuroscientist and Professor, Columbia Business School

Moran Cerf, a neuroscientist and professor at Columbia Business School, studies what happens in our brains when we talk, decide and get persuaded, and lately what happens when the other side of the conversation is AI. His research shows AI can read people remarkably well: from recordings of speed dates, it predicted who liked each other better than human observers did. The same skill worries him: we raise our guard when a person tries to sell us something, but not when AI does it in much the same way.


🎧 Episode overview
Moran's starting point is neural: in a human conversation, brain waves tune to each other and a nod or a glance carries much of the meaning, while a question-and-answer exchange with AI holds about a fifth of that information. His verdict on AI's influence is blunt: "We're a lot simpler than we think we are," and purchase times, flight bookings and browsing history are enough for AI to infer personality and nudge even political views. Eva pushes on teams that give AI agents human names: helpful in a Ferrari pit stop, he says, and a hindrance in a boardroom, where too often "if AI says do this, we end up doing this." On trust, he draws a line between the many mundane choices AI already handles well and the rare ones that define us, like a partner or a profession, and warns that our trust spills from the first to the second. His reason for hope is practical: when the world or our life changes, the AI twin trained on our past fails, and we get called back in.


💡 Key themes

  • Why AI can read and persuade people better than people can, and why we don't notice
  • When a human name for an AI agent helps a team, and when it distorts a decision
  • What the AI backlash has inherited from fifteen years of social media
  • Which choices to trust AI with, and how that trust spills over to the ones that define us
  • Whether control handed over for convenience comes back when life changes


👤 About the guest
Moran Cerf is a neuroscientist and professor at Columbia Business School whose work spans decision-making, persuasion and neural implants. He began by recording individual neurons to understand how the brain works, and several of his former PhD students now research AI at companies like Anthropic and OpenAI, which puts him right where brain science and AI meet.


⏱ Chapters

  • 00:00 The feedback loop AI can't join
  • 05:46 AI reads attraction, then learns to persuade
  • 16:01 From neural implants to brain-like AI
  • 29:22 Trust it with groceries, not with a partner
  • 37:07 Giving up control, and the retwin
  • 42:29 In-between moments


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