Yejin Choi, Wissner-Slivka Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington and Senior Research Director at the nonprofit Allen Institute for Artificial Intelligence.
William James Hall - 1st floor Lecture hall - Room 105
Yoobin Park, Ph.D., University of California, San Francisco
Topic: Thriving With Healthy Connections
Social relationships have a profound impact on mental and physical health. But what relationships do people pursue and why? What are the necessary ingredients for long-lasting, high-quality relationships? How can people leverage positive emotional interactions to feel closer to their valued social partners? My research employs a wide...
Beliefs have the power to drive human behavior—for better (e.g., social justice) and for worse (e.g., gun violence)—so it is essential to understand when, why, and how people latch on to certain beliefs over others. My research adopts an...
I will present the results from a variety of interconnected studies about intergroup conflict, the spread of (mis)information, and how these topics interact with digital technologies such as social media. First, I will present research showing how social identity motives — particularly...
Humans are an unusually successful species, numbering in the billions and inhabiting every habitat on the planet. An important determinant of this success is our adaptability, supported by a culturally-informed and extended period of developmental plasticity. My research examines this...
Topic: “Generating constructive disruption: How disadvantaged groups can negotiate social change in the face of resistance from the advantaged”
Recent decades have been characterized by the increasing occurrence and strength of grassroots social movements and large-scale collective action by historically disadvantaged...
William James Hall - 1st floor Lecture hall, Room 105
Maria Eckstein, Ph.D., Google Deep Mind
Topic: Understanding Human Learning and Decision Making Using Cognitive Models and Artificial Neural Networks
Computational modeling has been an indispensable tool for cognitive science, offering insights into otherwise elusive cognitive mechanisms. From Drift Diffusion Models to Reinforcement Learning (RL), Bayesian Inference, and beyond, computational models have not only illuminated intricate cognitive processes, but also...