Symposium - Paradox: Frames and Biases in Art and AI

Symposium
Paradox: Frames and Biases in Art and AI

Jan. 28, 5:30–8:30pm

RSVP on Facebook

Organized by Eunsu Kang and Elizabeth Chodos

Panel members: Manuela Veloso, Alexandra Chouldechova, Sey Min, Jillian Mayer, and Kerry Doran.

This panel discussion explores the ways bias is inherently built into the structure and function of Machine Learning. In order to make predictions or identify patterns, AI requires that a person set specific instructions that have the potential to reinforce bias and oppressive social structures, particularly when ML is being used in everything from policing to determining someone’s credit score. This panel will also explore the role that contemporary art can play in challenging and refiguring these biases by calling into question the frameworks underpinning our assumptions. As ML and AI continue to influence more aspects of everyday life, conversations around how we can use these tools to undo harmful biases, as opposed to reinforcing them, is increasingly urgent.