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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