Analyzing Biased Datasets and Injustice in AI

Coded bias, intersectionality in AI, and computer vision: Founder of the Algorithmic Justice League Joy Buolamwini talks to host Jon Krohn about the impact of exclusion and inclusion in datasets, the need to address intersectionality when identifying racial, age, or gender-based prejudice in machine learning tools, protections for artists and creative practitioners against AI, and the role that AI may have in combating systemic racism.

This episode is brought to you by Gurobi, the Decision Intelligence Leader,  and by CloudWolf, the Cloud Skills platform. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• What coded bias is [06:49]
• The problem with bias in machine learning datasets [18:41]
• The Incoding Movement [42:08]
• About the Pilot Parliaments Benchmark [52:07]
• Ethics and the future of AI [1:20:10]
• The potential for AI to end systemic racism [1:32:59]

Additional materials: www.superdatascience.com/727