A practical approach to addressing bias in artificial intelligence – Press and Guide

Over the past decade, there has been no shortage of examples of human bias creeping into AI processes.

In 2020, Robert Williams, a Black Farmington Hills resident, was arrested and jailed after a police facial recognition algorithm mistakenly identified him as a man stealing from security footage, a known weakness these systems have for accurately identify people with darker skin. In 2019, researchers showed that a software system widely used by hospitals to identify patient risks preferred white people for many types of care. A few years ago, Amazon mostly abandoned a system it was using to screen job applicants when it found it was consistently favoring men over women.

The way in which human biases are integrated into AI algorithms is a complicated phenomenon.

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