Joint AI-SDM Center / S3D Seminar - Tom Griffiths

— 1:00pm

Location:
In Person and Virtual - ET - ASA Conference Room, Gates Hillman 6115 and Zoom

Speaker:
TOM GRIFFITHS , Henry R. Luce Professor of Information Technology, Consciousness and Culture, Departments of Psychology and Computer Science, Director, Computational Cognitive Science Lab, Princeton University
https://cocosci.princeton.edu/tom/index.php

Using Machine Learning and Psychology to Predict and Understand Human Decisions

Machine learning methods provide increasingly powerful tools for generating predictions about human behavior. However, simply using off the shelf methods to generate predictions potentially misses opportunities to benefit from and contribute to the psychological literature. 

In this talk I will discuss three ways in which theory and data can interact through machine learning: using theories to pretrain machine learning models; using theories to constrain machine learning models; and using unconstrained machine learning models to critique explanatory theories. I will illustrate these cases with examples from the study of human decision-making, discussing risky choice, moral judgments, behavioral game theory, and open-ended decision-making, and also highlight some recent work using large language models to predict human decisions. 

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Tom Griffiths is the Henry R. Luce Professor of Information Technology, Consciousness and Culture in the Departments of Psychology and Computer Science at Princeton University. His research explores connections between human and machine learning, using ideas from statistics and artificial intelligence to understand how people solve the challenging computational problems they encounter in everyday life. He has made contributions to the development of Bayesian models of cognition, probabilistic machine learning, nonparametric Bayesian statistics, and models of cultural evolution, and his recent work has demonstrated how methods from cognitive science can shed light on modern artificial intelligence systems. 

Tom completed his PhD in Psychology at Stanford University in 2005, and taught at Brown University and the University of California, Berkeley before moving to Princeton. He has received awards for his research from organizations ranging from the American Psychological Association to the National Academy of Sciences and is a co-author of the book Algorithms to Live By, introducing ideas from computer science and cognitive science to a general audience. 

REGISTER→connecting information will be provided upon registration.

Event Website:
https://www.cmu.edu/ai-sdm/events/index.html

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