Betsy Anne Williams|Catherine Brooks|Yotam Shmargad
How Algorithms Discriminate Based on Data They Lack: Challenges, Solutions, and Policy Implications
University of Arizona|University of Arizona|University of Arizona
abstract organizations often employ datadriven models inform decisions significant impact peoples lives eg university admissions hiring order protect peoples privacy prevent discrimination decisionmakers may choose delete avoid collecting social category data like sex race article argue censoring exacerbate discrimination making biases difficult detect begin detailing computerized decisions lead biases absence social category data contexts may even sustain biases arise random chance show proactively using social category data help illuminate combat discriminatory practices using cases education employment lead strategies detecting preventing discrimination conclude discrimination occur sociotechnical system someone decides use algorithmic process inform decisionmaking offer set broader implications researchers policymakers