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I love dresses. Not on me, of course — I’m not nearly elegant enough to pull it off. Nevertheless, to me, dresses are one of the most elegant pieces of clothing ever invented.
And I like them even more when they change colors. Well, they don’t really change colors — it’s the way we perceive the colors that can change. You remember that dress that looked black and blue to some people, and white and gold to others? Well that’s exactly what we’ll dive into and explain in this episode.
Why do we literally see the world differently? Why does that even happen beyond our consciousness, most of the time? And cherry on the cake: how on Earth could this be related to… priors?? Yes, as in Bayesian priors!
Pascal Wallisch will shed light on all these topics in this episode. Pascal is a professor of Psychology and Data Science at New York University, where he studies a diverse range of topics including perception, cognitive diversity, the roots of disagreement and psychopathy.
Originally from Germany, Pascal did his undergraduate studies at the Free University of Berlin. He then received his PhD from the University of Chicago, where he studied visual perception.
In addition to scientific articles on psychology and neuroscience, he wrote multiple books on scientific computing and data science. As you’ll hear, Pascal is a wonderful science communicator, so it's only normal that he also writes for a general audience at Slate or the Creativity Post, and has given public talks at TedX and Think and Drink.
Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !
Thank you to my Patrons for making this episode possible!
Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R and Nicolas Rode.
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In our conversation, Pascal Wallisch, a professor of Psychology and Data Science at New York University, shared about his research on perception, cognitive diversity, the roots of disagreement, and psychopathy.
Pascal did his undergraduate studies at the Free University of Berlin and then received his PhD from the University of Chicago, where he studied visual perception. Pascal is also a TedX, Think and Drink speaker, and writer for Slate and Creativity Post.
We discussed Pascal's origin story, his current work on cognitive diversity, and the importance of priors in perception.
Pascal used the example of "the Dress" picture that went viral in 2015, where people saw either black and blue or white and gold. He explained how prior experience and knowledge can affect how people perceive colors and motion, and how priors can bias people for action.
We discussed to what extent the brain might be Bayesian and what functions are probably not so well described in bayesian terms.
Pascal also discussed how priors can be changed through experience and exposure.
Finally, Pascal emphasized that people have different priors and perspectives, and that understanding these differences is crucial for creating a more diverse and inclusive society.
Please note that the following transcript was generated automatically and may therefore contain errors. Feel free to reach out if you’re willing to correct them.