Joshua Song authored an article in the Michigan Technology Law Review about the best way to establish fair recidivism prediction instruments (RPI). In the article, Joshua proposes that false positive parity is the best statistical measure of parity for use in assessing the fairness of RPIs and aims to answer two questions:
1. What are the most essential factors for substantiating fairness in the criminal justice system and are thus necessary conditions in any algorithmic bias measurement?
2. Which statistical measure of parity best meets these necessary conditions in assessing fairness in RPIs?
Read the full article on MTLR.