Machine Learning Bias and Fairness with Timnit Gebru and Margaret Mitchell: GCPPodcast 114
Original post: https://www.gcppodcast.com/post/episode-114-machine-learning-bias-and-fairness-with-timnit-gebru-and-margaret-mitchell/
This week, we dive into machine learning bias and fairness from a social and technical perspective with machine learning research scientists Timnit Gebru from Microsoft and Margaret Mitchell (aka Meg, aka M.) from Google. They share with Melanie and Mark about ongoing efforts and resources to address bias and fairness including diversifying datasets, applying algorithmic techniques and expanding research team expertise and perspectives. There is not a simple solution to the challenge, and they give insights on what work in the broader community is in progress and where it is going.
Original post: https://www.gcppodcast.com/post/episode-114-machine-learning-bias-and-fairness-with-timnit-gebru-and-margaret-mitchell/
This week, we dive into machine learning bias and fairness from a social and technical perspective with machine learning research scientists Timnit Gebru from Microsoft and Margaret Mitchell (aka Meg, aka M.) from Google. They share with Melanie and Mark about ongoing efforts and resources to address bias and fairness including diversifying datasets, applying algorithmic techniques and expanding research team expertise and perspectives. There is not a simple solution to the challenge, and they give insights on what work in the broader community is in progress and where it is going.
