Title:
Let’s Talk about Bias and Diversity in Data, Software, and Institutions
Let’s Talk about Bias and Diversity in Data, Software, and Institutions
Author(s)
Deng, Tiffany
Desai, Deven
Gontijo Lopes, Raphael
Isbell, Charles L.
Desai, Deven
Gontijo Lopes, Raphael
Isbell, Charles L.
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Editor(s)
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Abstract
Bias and lack of diversity have long been deep-rooted problems across industries. We discuss how these issues impact data, software, and institutions, and how we can improve moving forward. The panel will feature thought leaders from Google, Georgia Tech, and Queer in AI, who will together answer questions like "What implications and problems exist or will exist if the tech workforce does not become more diverse?" and "How does anyone make sure they are not introducing their bias into a given system? What questions should we be asking or actions should we be taking to avoid this?"
Sponsor
Date Issued
2020-11-20
Extent
54:00 minutes
Resource Type
Moving Image
Resource Subtype
Lecture