2022

The four-fifths rule is not disparate impact: a woeful tale of epistemic trespassing in algorithmic fairness

Watkins, Elizabeth Anne, McKenna, Michael, Chen, Jiahao

Understand

Computer scientists are trained to create abstractions that simplify and generalize.

However, a premature abstraction that omits crucial contextual details creates the risk of epistemic trespassing, by falsely asserting its relevance into other contexts.
We study how the field of responsible AI has created an imperfect synecdoche by abstracting the four-fifths rule (a.k.a.
the 4/5 rule or 80% rule), a single part of disparate impact discrimination law, into the disparate impact metric.

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