26 min listen
Causal Conceptions of Fairness and their Consequences with Sharad Goel - #586
FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Causal Conceptions of Fairness and their Consequences with Sharad Goel - #586
FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
ratings:
Length:
37 minutes
Released:
Aug 8, 2022
Format:
Podcast episode
Description
Today we close out our ICML 2022 coverage joined by Sharad Goel, a professor of public policy at Harvard University. In our conversation with Sharad, we discuss his Outstanding Paper award winner Causal Conceptions of Fairness and their Consequences, which seeks to understand what it means to apply causality to the idea of fairness in ML. We explore the two broad classes of intent that have been conceptualized under the subfield of causal fairness and how they differ, the distinct ways causality is treated in economic and statistical contexts vs a computer science and algorithmic context, and why policies are created in the context of causal definitions are suboptimal broadly.
The complete show notes for this episode can be found at twimlai.com/go/586
The complete show notes for this episode can be found at twimlai.com/go/586
Released:
Aug 8, 2022
Format:
Podcast episode
Titles in the series (100)
This Week in ML & AI - 6/24/16: Dueling Neural Networks at ICML, Plus Training a Robotic Housekeeper: This Week in Machine Learning & AI brings you the… by The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)