Building Reliable AI Models Requires Understanding the People Behind the Datasets

August 2, 2023


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<5 mins
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Presented by School of Kinesiology

Social media algorithms and AI systems rely on data to learn what is offensive. But who’s behind the data, and how do their backgrounds influence their decisions? A recent study by U-M School of Information assistant professor David Jurgens and PhD candidate Jiaxin Pei suggests that the backgrounds of data annotators — the people labeling texts, videos, and online media — matter a lot.

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