Showing 1–20 of 24 results
/ Date/ Name
May 13, 2021An Empirical Comparison of Bias Reduction Methods on Real-World Problems in High-Stakes Policy SettingsJan 24, 2020Case Study: Predictive Fairness to Reduce Misdemeanor Recidivism Through Social Service InterventionsJan 16, 2019Artificial Intelligence for Social GoodJun 1, 2020A Machine Learning System for Retaining Patients in HIV CareJul 12, 2022A Conceptual Framework for Using Machine Learning to Support Child Welfare DecisionsJun 24, 2022On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML MethodsMar 2, 2022Faking feature importance: A cautionary tale on the use of differentially-private synthetic dataMay 15, 2019A Clinical Approach to Training Effective Data ScientistsOct 27, 2020Explainable Machine Learning for Public Policy: Use Cases, Gaps, and Research DirectionsDec 5, 2020Empirical observation of negligible fairness-accuracy trade-offs in machine learning for public policyAug 26, 2020Bandit Data-Driven OptimizationAug 27, 2020Mapping New Informal Settlements using Machine Learning and Time Series Satellite Images: An Application in the Venezuelan Migration CrisisSep 17, 2025Breaking the Cycle of Incarceration With Targeted Mental Health Outreach: A Case Study in Machine Learning for Public PolicySep 29, 2023Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and ToolsMay 9, 2024Aequitas Flow: Streamlining Fair ML ExperimentationDec 21, 2018Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and EffectivenessSep 16, 2017Applying Machine Learning Methods to Enhance the Distribution of Social Services in MexicoMay 9, 2018Using Machine Learning to Assess the Risk of and Prevent Water Main BreaksNov 14, 2018Aequitas: A Bias and Fairness Audit ToolkitJul 30, 2020A Recommendation and Risk Classification System for Connecting Rough Sleepers to Essential Outreach Services