AIAug 23, 2024

Temporal Fairness in Decision Making Problems

arXiv:2408.13208v11 citationsh-index: 19
Originality Incremental advance
AI Analysis

This work addresses fairness in decision-making for domains requiring historical context, but it is incremental as it builds on existing fairness formulations.

The authors tackled the problem of fairness in decision-making by introducing temporal fairness, which considers the fairness of past decisions over time, and proposed three optimization-based approaches that were qualitatively evaluated in four domains against a non-temporal baseline.

In this work we consider a new interpretation of fairness in decision making problems. Building upon existing fairness formulations, we focus on how to reason over fairness from a temporal perspective, taking into account the fairness of a history of past decisions. After introducing the concept of temporal fairness, we propose three approaches that incorporate temporal fairness in decision making problems formulated as optimization problems. We present a qualitative evaluation of our approach in four different domains and compare the solutions against a baseline approach that does not consider the temporal aspect of fairness.

Foundations

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