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Since it lacks personal details, synthetic data can help insurers address a number of challenges including regulatory compliance and data-set bias. (Lia Kolyrina/Shutterstock) Since it lacks personal details, synthetic data can help insurers address a number of challenges including regulatory compliance and data-set bias. (Lia Kolyrina/Shutterstock)

Come 2022, 85% of algorithms will be erroneous due to bias, according to Gartner.

Most of the blame lies with the data sets used to train AI models, which often lack enough data representation for women, people of color and other minority groups.

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