What if the training data for AI are not only biased, but also incomplete? In a new proposal, Catherine Tucker makes the case for including algorithmic exclusion—failure or harm arising from insufficient input data—in AI policies and regulations.
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Artificial intelligence and algorithmic exclusion - The Hamilton Project
In this proposal, Catherine Tucker makes the case for including algorithmic exclusion, defined as failure or harm arising from insufficient input data, in AI policies and regulations.
