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The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice
The ``impossibility theorem'' -- which is considered foundational in algorithmic fairness literature -- asserts that there must be trade-offs between common notions of fairness and performance when fitting statistical models, except in two special cases: when the prevalence of the outcome being predicted is equal across groups, or when a perfectly accurate predictor is used.
Argumentative Topology: Finding Loop(holes) in Logic
Advances in natural language processing have resulted in increased capabilities with respect to multiple tasks.
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