TL;DR
FairSight is a visual analytics system designed to help understand, diagnose, and mitigate biases in data-driven decision making to promote fairness, demonstrated through case and user studies.
Contribution
It introduces a novel visual analytic tool that operationalizes fairness notions in decision pipelines, bridging the gap between fairness algorithms and real-world practice.
Findings
Effective in diagnosing biases in decision processes
Helps achieve fairer outcomes in case studies
User study confirms usability and utility
Abstract
Data-driven decision making related to individuals has become increasingly pervasive, but the issue concerning the potential discrimination has been raised by recent studies. In response, researchers have made efforts to propose and implement fairness measures and algorithms, but those efforts have not been translated to the real-world practice of data-driven decision making. As such, there is still an urgent need to create a viable tool to facilitate fair decision making. We propose FairSight, a visual analytic system to address this need; it is designed to achieve different notions of fairness in ranking decisions through identifying the required actions -- understanding, measuring, diagnosing and mitigating biases -- that together lead to fairer decision making. Through a case study and user study, we demonstrate that the proposed visual analytic and diagnostic modules in the system…
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