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PAIR AI Explorables | Is the problem in the data? Examples on Fairness, Diversity, and Bias.
Apr 15, 2021
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Yannic Kilcher
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PAIR AI Explorables
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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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
Category: Research Paper
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