Award-Winning Research Highlights Challenges and Opportunities for More Reliable Human-AI Decision-Making

Researchers with the Northwestern Center for Advancing Safety of Machine Intelligence (CASMI) have investigated threats to validity and reliability in human-AI decision-making and have demonstrated how new methods may help address these challenges.

The team from Carnegie Mellon University (CMU) – comprised of Luke Guerdan, PhD student at the CMU Human-Computer Interaction Institute; Amanda Coston, PhD student in machine learning and public policy; Kenneth Holstein, Assistant Professor at the Human-Computer Interaction Institute and principal investigator for the CASMI project, “Supporting Effective AI-Augmented Decision-Making in Social Contexts”; and Steven Wu, Assistant Professor at the Software and Societal Systems Department – won a best paper award in June at the Association for Computing Machinery Conference on Fairness, Accountability, and Transparency (ACM FAccT) for their research paper, “Counterfactual Prediction Under Outcome Measurement Error.”

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