Fairness in legal AI is defined by stakeholders not technicians

Evidence

No matter how well-collected the criminal justice data, any technology that builds upon it must be vetted by experts who can contextualize the data. This is necessary because, at the least, technology should operate fairly, and fairness must be defined by key stakeholders. Once it is so defined, then context becomes vital for making sure that the legal technology employs the fairness definition that the key stakeholders think is the appropriate one to use (see Selbst et al., 2019). For example, how criminal records should be weighed in analyses of future criminal risk is a policy question. Once it is answered by policy experts, then the instantiation will require careful reworking of the algorithm. — Joseph Avery, Jim Sidanius, Joel Cooper, Gregory Davis, Amanda N., Bias in the Law, 1182

Categorization

• SEED: Article angle: who gets to define fairness in criminal-justice algorithms — the policy question hiding inside every AI fairness metric.