Steven Shaw, PhD
Wharton Postdoctoral Researcher
I study the biological, psychological, and technological forces that drive decisions, from consumption to mate choice. Integrating emerging technologies, novel data, and interdisciplinary methods, I examine how innovations—from AI to genomics—reshape psychology and society.
I am a Postdoctoral Researcher in the Marketing Department at
The Wharton School of the University of Pennsylvania. My work has been covered in TIME, The Economist, Forbes, The Globe and Mail, BBC, The New York Times, Wall Street Journal, Ars Technica, Scientific American, and Vox, among others. I have appeared on radio/podcasts, including: Marketplace Tech, You Are Not So Smart,
and Wharton's Ripple Effect.
My latest paper introduces Tri-System Theory of Cognition, and demonstrates the rise of cognitive surrender: deference to AI without verification. Other work introduces biological age (BioAge) as a next-generation demographic variable, using epigenetic clocks to reveal insights into the aging consumer. Another project explores how large language models (LLMs) can enhance the generalizability of experiments through the automated creation of stimulus universes. I also study consumer neuroscience, including how neural activity can forecast market trends.
I hold a Ph.D. in Marketing and an M.A. in Statistics from the University of Michigan, Ann Arbor and dual B.Sc. degrees in Genetics & Psychology and Animal Behaviour from the University of Western Ontario, Canada.
The Wharton School of the University of Pennsylvania. My work has been covered in TIME, The Economist, Forbes, The Globe and Mail, BBC, The New York Times, Wall Street Journal, Ars Technica, Scientific American, and Vox, among others. I have appeared on radio/podcasts, including: Marketplace Tech, You Are Not So Smart,
and Wharton's Ripple Effect.
My latest paper introduces Tri-System Theory of Cognition, and demonstrates the rise of cognitive surrender: deference to AI without verification. Other work introduces biological age (BioAge) as a next-generation demographic variable, using epigenetic clocks to reveal insights into the aging consumer. Another project explores how large language models (LLMs) can enhance the generalizability of experiments through the automated creation of stimulus universes. I also study consumer neuroscience, including how neural activity can forecast market trends.
I hold a Ph.D. in Marketing and an M.A. in Statistics from the University of Michigan, Ann Arbor and dual B.Sc. degrees in Genetics & Psychology and Animal Behaviour from the University of Western Ontario, Canada.
