What question did this study set out to answer?

This research aims to define and analyze the concept of algorithmic fairness and its implications on decision-making processes.

September 23, 2016Open Access

On the (im)possibility of fairness

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Formalizing different notions of algorithmic fairness to clarify assumptions in decision-making processes.

This research aims to define and analyze the concept of algorithmic fairness and its implications on decision-making processes.
Introduced a mathematical setting to formalize algorithmic fairness distinctions.
Characterized the observed and decision spaces along with the construct space.
Analyzed the assumptions required for fair algorithms based on the mapping between these spaces.
Identified that various fairness mechanisms require distinct mapping assumptions.
Showed that future studies must clarify how unobservable constructs relate to observable decisions.

Friedler et al. (2016) studied this question.

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