A technique to improve both fairness and accuracy in artificial intelligence

Methods that make a machine-learning model’s predictions more accurate overall can reduce accuracy for underrepresented subgroups. A new approach can help.

accuracy algorithms artificial artificial intelligence data diversity and inclusion ethics fairness human-computer interaction intelligence machine learning mit schwarzman college of computing national science foundation (nsf) race and gender research research laboratory of electronics school of engineering