Deep Dive Episode 114 – Is Artificial Intelligence Biased? And What Should We Do About It?
Regulatory Transparency Project's Fourth Branch Podcast
Journalists and academics seem convinced that artificial intelligence is often biased against women and racial minorities. If Washington’s new facial recognition law is a guide, legislators see the same problem. But is it true? It’s not hard to find patterns in AI decisions that have a disparate impact on protected groups. Is this bias? And if so, whose?
Do we assume the worst about decisions with a disparate impact – applying a kind of misanthropomorphism to the machine – or can we objectively analyze the factors behind the decisions? If bias boils down to not producing proportionate results for each protected class, is the only remedy to impose a “proportionate result” constraint on AI processing – essentially imposing racial, ethnic, and gender quotas on every corner of life that is touched by AI?
Featuring:
- Stewart Baker, Partner, Steptoe & Johnson LLP
- Curt Levey, President, Committee for Justice
- Nicholas Weaver, Researcher, International Computer Science Institute and Lecturer, UC Berkeley
Visit our website – www.RegProject.org – to learn more, view all of our content, and connect with us on social media.