The Unintentional Consequences of Digital Redlining

2min Snip

00:00

Play full episode

Summary

Transcript

Episode notes

In the U.S., financial institutions would redline, which basically mean they would outline certain areas like communities and say, yeah, let's not give good rates or lend in these areas. Basically picking on specific minority groups and people of color and things like that. And so basically they were drawing a map and saying, yeah, if you live in this zip code or this area, yeah, we're basically going to treat you like a second class citizen. We might not give you as good of a rate. I believe it was proven they did this and it is now, of course, illegal to do that. But it doesn't mean that the legacy of that is not felt because

Ethics in AI is a broad, deep, and tough subject. It's also, arguably, one of the most important subjects for analysts, data scientists, and organizations overall to deliberately and determinedly tackle as a standard part of how they do work. On this episode, Renée Cummings, Professor of Practice in Data Science and Data Activist in Residence at the University of Virginia (among many other roles), joined us for a discussion of the subject. Her knowledge of the topic is as deep as her passion for it, and both are bordering on the limitless, so it was an incredibly informative chat! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.