4 citations · 10 across the 8 of their papers we have counts for
9 papers
Learning Who to Treat When Treatment is Missing
Johnna Sundberg, Rayid Ghani, Eli Ben-Michael +1
Policy learning methods are increasingly used to inform treatment allocation under budget constraints. Most proposed methods assume complete treatment data, yet applications freque…
Bridging Predictions and Interventions: An Integrated Framework for Automated Decision-Systems
Inioluwa Deborah Raji, Lydia T. Liu, Angela Zhou +27
Automated decision systems (ADS) leverage predictions about individual future outcomes to inform consequential decision-making in organizational settings. Across various settings -…
Bridging Prediction and Intervention Problems in Social Systems
Lydia T. Liu, Inioluwa Deborah Raji, Angela Zhou +32
Many automated decision systems (ADS) are designed to solve prediction problems -- where the goal is to learn patterns from a sample of the population and apply them to individuals…
Longitudinal Causal Inference with Selective Eligibility
Zhichao Jiang, Eli Ben-Michael, D. James Greiner +2
Dropout poses a significant challenge to causal inference in longitudinal studies with time-varying treatments. However, existing research does not simultaneously address dropout a…
Intervention effects based on potential benefit
Alexander W. Levis, Eli Ben-Michael, Edward H. Kennedy
Optimal treatment rules are mappings from individual patient characteristics to tailored treatment assignments that maximize mean outcomes. In this work, we introduce a conditional…
Does AI help humans make better decisions? A statistical evaluation framework for experimental and observational studies
Eli Ben-Michael, D. James Greiner, Melody Huang +3
The use of Artificial Intelligence (AI), or more generally data-driven algorithms, has become ubiquitous in today's society. Yet, in many cases and especially when stakes are high,…
Bayesian Safe Policy Learning with Chance Constrained Optimization: Application to Military Security Assessment during the Vietnam War
Zeyang Jia, Eli Ben-Michael, Kosuke Imai
Algorithmic decisions and recommendations are used in many high-stakes decision-making settings such as criminal justice, medicine, and public policy. We investigate whether it wou…
Safe Policy Learning under Regression Discontinuity Designs with Multiple Cutoffs
Yi Zhang, Eli Ben-Michael, Kosuke Imai
The regression discontinuity (RD) design is widely used for program evaluation with observational data. The primary focus of the existing literature has been the estimation of the…
Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment
Eli Ben-Michael, D. James Greiner, Kosuke Imai +1
Algorithmic recommendations and decisions have become ubiquitous in today's society. Many of these data-driven policies, especially in the realm of public policy, are based on know…