On Algorithmic decision making
No matter how much data we collect, two people who look the same to the algorithm can always end up making different choices.
Two definitions of fairness:
- keep the error rates comparable between groups, and
- treat people with the same risk scores in the same way.
Both of these definitions are totally defensible! But satisfying both at the same time is impossible.
Relevant reads on algorithms and algorithmic decision making: To Live in their Utopia, Algorithms of Oppression