PAIR AI Explorables | Is the problem in the data? Examples on Fairness, Diversity, and Bias.

In the recurring debate about bias in Machine Learning models, there is a growing argument saying that "the problem is not in the data", often citing the influence of various choices like loss functions or network architecture. In this video, we take a look at PAIR's AI Explorables through the lens of whether or not the bias problem is a data problem.

OUTLINE:
0:00​ - Intro & Overview
1:45​ - Recap: Bias in ML
4:25​ - AI Explorables
5:40​ - Measuring Fairness Explorable
11:00​ - Hidden Bias Explorable
16:10​ - Measuring Diversity Explorable
23:00​ - Conclusion & Comments

AI Explorables: https://pair.withgoogle.com/explorables/​

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