We Can Build an Algorithm to Help De-Bias Datasets

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In one of your lectures, you talked about the fact that there's a belief that we can de-bias datasets. What we need to do is start with our thinking, that understanding of the history, bringing that ethical approach and yes, we may be able to get technical support from an algorithm. One of the things I always say as well is that we never want to reach your place where we've got to deploy an algorithm or design an algorithm to teach us what it means to be human again. So let's bring our collective intelligence to the space. Let's bring that emotional intelligence to thespace. Let us build big things, but let us build ethical things that ensure that what

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.