Podcast: Dissecting Racial Bias from AI and Machine Learning

On an episode of Abt Associates’ The Intersect podcast, Abt’s Laura Peck and Jason Brinkley sit down with Eric Tishler to discuss how racial bias pervades AI and machine learning. Despite the seemingly unbiased processing of intelligent software, AI and machine learning platforms are trained on databases made by humans with their own implicit biases. This has real-world impacts on marginalized people.

Accordign to Peck, “We know that bias is inherent in the kind of data that we use in public policy research as you mentioned, Eric. The data that we collect to understand the world and the people in it reflects underpinning discrimination in society and longstanding inequalities. So, why would we think that artificial intelligence and related machine learning tools could rid the data of that bias? I think that if we want to eliminate bias from surfacing in the results of any data analysis, we need to be deliberate in that being a goal of the analysis.”

Read the full transcript or listen to the podcast by clicking here.

(Source: Abt Associates, February 17^th, 2021)