Today we welcome Daniel Simons and Christopher Chabris to the podcast.

Daniel Simons is a professor of psychology at the University of Illinois where he heads the Visual Cognition Laboratory. His research explores the limits of awareness and memory, the reasons why we often are unaware of those limits, and the implications for our personal and professional lives.

Christopher Chabris is professor and co-director of the Behavioral and Decision Sciences Program at Geisinger Health System. He is also faculty co-director of Geisinger's Behavioral Insights Team. From 2014 to 2017, he wrote a monthly column called GAME ON for The Wall Street Journal. His essays have been published in several media outlets.

Daniel and Christopher met at Harvard University in 1997, where they began to collaborate on research. In 2004 they shared the Ig Nobel Prize in Psychology, awarded for The Invisible Gorilla experiment. Together, they co-authored the New York Times bestselling book of the same name. Their latest book is called Nobody's Fool: Why We Get Taken In and What We Can Do About It.

In this episode I talk to Daniel and Christopher about scams and how NOT to get scammed! With enough information and persuasion, anybody can fall for a scheme. According to Daniel and Christopher, certain cognitive biases can make us vulnerable to deception. To help us outsmart con artists, they elaborate the different types of scams and how they work, all the while giving us tools to navigate shady situations.

Website: dansimons.com & chabris.com

Twitter: @profsimons & @cfchabris

Topics

03:20 Nobody’s Fool

07:54 Using AI for deception

10:13 The truth bias

12:42 Fixed belief bias

16:40 The possibility grid

22:27 Scamming through social media

24:21 The Nigerian email scam

27:19 Scam baiting

29:01 Bernie Madoff’s Ponzi scheme

35:16 Are mediums scammers?

36:47 Why do people ignore red flags?

38:59 The Tinder Swindler and romance scams

44:05 Highly successful people get scammed too

47:17 When to be skeptical

54:37 Accept less, check more

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