Which Demographic Features Are Relevant for Individual Fairness Evaluation of U.S. Recidivism Risk Assessment Tools?
This addresses fairness evaluation for recidivism risk assessment tools, which is crucial for legal and ethical applications in the U.S., but it is incremental as it builds on existing fairness criteria without introducing new methods.
The study tackled the problem of operationalizing individual fairness for recidivism risk assessment tools by conducting a human subjects experiment to determine relevant demographic features, concluding that age and sex should be considered while race should be ignored.
Despite its constitutional relevance, the technical ``individual fairness'' criterion has not been operationalized in U.S. state or federal statutes/regulations. We conduct a human subjects experiment to address this gap, evaluating which demographic features are relevant for individual fairness evaluation of recidivism risk assessment (RRA) tools. Our analyses conclude that the individual similarity function should consider age and sex, but it should ignore race.