Campus Event: "Understanding Racial Bias in Algorithms"

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September 25, 2020
12:00PM - 1:00PM
Location
Online

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Add to Calendar 2020-09-25 12:00:00 2020-09-25 13:00:00 Campus Event: "Understanding Racial Bias in Algorithms" The Program on Data and Governance in the Moritz College of Law, with support from the Translational Data Analytics Institute, is hosting a webinar on "Understanding Racial Bias in Algorithms" as part of its lecture series Data Points: Ideas on Data, Law and Society.  About the Event In the digital society, algorithms can be a major source of implicit bias and structural racism. Racial, gender, and other types of harmful bias can be baked into the algorithms that companies use to decide who gets jobs, loans, or insurance, and that government uses to determine who gets paroled or who is placed on the no-fly list. Identifying and preventing the racial bias in these algorithms is one of the key civil rights challenges of our era. In this event, a panel of Ohio State professors and researchers will help us to understand racial bias in algorithms – what it is, how it happens, what harms result, and how we can work to eliminate it. Panelists Tanya Berger-Wolf | Faculty Director, Translational Data Analytics Institute; Professor, Computer Science and Engineering; Evolution, Ecology, and Organismal Biology; and Electrical and Computer Engineering Kelly Capatosto | Senior Data and Policy Specialist, Kirwan Institute for the Study of Race and Ethnicity Sean Hill | Assistant Professor, Moritz College of Law Christopher Stewart | Associate Professor, Computer Science and Engineering Dennis Hirsch (moderator) | Professor of Law, Moritz College of Law, and Director, Program on Data and Governance   More Information and Registration Online Center for Ethics and Human Values cehv@osu.edu America/New_York public
Description

The Program on Data and Governance in the Moritz College of Law, with support from the Translational Data Analytics Institute, is hosting a webinar on "Understanding Racial Bias in Algorithms" as part of its lecture series Data Points: Ideas on Data, Law and Society

About the Event

In the digital society, algorithms can be a major source of implicit bias and structural racism. Racial, gender, and other types of harmful bias can be baked into the algorithms that companies use to decide who gets jobs, loans, or insurance, and that government uses to determine who gets paroled or who is placed on the no-fly list. Identifying and preventing the racial bias in these algorithms is one of the key civil rights challenges of our era.

In this event, a panel of Ohio State professors and researchers will help us to understand racial bias in algorithms – what it is, how it happens, what harms result, and how we can work to eliminate it.

Panelists

Tanya Berger-Wolf | Faculty Director, Translational Data Analytics Institute; Professor, Computer Science and Engineering; Evolution, Ecology, and Organismal Biology; and Electrical and Computer Engineering

Kelly Capatosto | Senior Data and Policy Specialist, Kirwan Institute for the Study of Race and Ethnicity

Sean Hill | Assistant Professor, Moritz College of Law

Christopher Stewart | Associate Professor, Computer Science and Engineering

Dennis Hirsch (moderator) | Professor of Law, Moritz College of Law, and Director, Program on Data and Governance

 

More Information and Registration

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