Eye on A.I.: Decoding the Bias

Sasha Costanza-Chock, Shalini Kantayya, Safiya Noble and Kishawna Peck speak with Ethan Zuckerman to discuss biases, equity, transparency, and governance as they  relate to machine learning.  

In the 2020 film Coded Bias, filmmaker Shalini Kantayya explores the fallout of MIT Media Lab researcher Joy Buolamwini’s discovery that facial recognition does not see dark-skinned faces accurately, and her journey to push for the first-ever legislation in the U.S. to govern against bias in the algorithms that impact us all.

In this panel discussion, leading experts working in the field of machine learning discuss the underlying prejudices embedded in computer code and how we might unravel these predispositions and ensure all humans are treated equally by both human and machine.  The discussion will focus on racial and gender biases in artificial intelligence (A.I.) and how it affects our day to day living. 

Registration is required.  

As a component of the program, we encourage participants to view Coded Bias.  The film is available to current MIT community members here; it is also available to members of the general public on Netflix.  

The MIT Libraries is committed to accessibility.  Please email us if you would like to request accommodation to participate in this program.  Please let us know as far in advance as possible and we will do our best to meet your request. 

This event is presented in collaboration with the Toronto Public Library and is part of TPL's On Civil Society series.