Model Multiplicity: Opportunities, Concerns, and Solutions
The authors explore the implications of model multiplicity – the phenomenon in the development of machine learning models that produces several model specifications for a given task that differ in various ways but deliver equal accuracy.
Emily Black, Manish Rhagavan, and Solon Barocas; FAccT ’22
June 2022