Machine-Made Decisions: Consequences of Consistency
Automated algorithm-driven decision-making systems are increasingly replacing humans in areas as varied as HR hiring, loan applications, insurance brokerage and even routine medical diagnostics. In some contexts, such as employment, decision making based on arbitrary criteria is legal, and in others such as criminal sentencing, it is not. As algorithms replace human deciders, what are the considerations and consequences for decisions that are made at scale? And what are the moral or ethical implications?
Our guest for this episode has a unique vantage point from which to share a perspective on these questions. Kathleen Creel is the Embedded EthiCS fellow at Stanford University, based in the Center for Ethics in Society (EiS) and the Institute for Human-Centered Artificial Intelligence (HAI). Her work is informed by a multidisciplinary background steeped in philosophy and computer science.
Hosted by: Alexa Raad & Leslie Daigle
- The Algorithmic Leviathan: Arbitrariness, Fairness, and Opportunity in Algorithmic Decision-Making Systems
- Transparency In Complex Computational Systems: preprint published version
- On Fairness, Diversity and Randomness in Algorithmic Decision Making
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