Researchers Build Framework To Avoid Machine Learning’s “Undesirable Outcomes”
Researchers at Stanford and the University of Massachusetts Amherst have introduced a framework for designing machine learning (ML) algorithms that make it easier for potential users to specify safety and fairness constraints. Details of the framework were recently published in Science (DOI: 10.1126/science.aag3311).
By Benjamin Ross, Senior Editor, AI Trends