Algorithmic fairness requires stakeholder-defined meaning plus expert contextual vetting

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). — Joseph Avery, Jim Sidanius, Joel Cooper, Gregory Davis, Amanda N., Bias in the Law, 1182

Categorization

• XREF: Fairness as a contested, stakeholder-defined construct parallels how professed egalitarian conviction diverges from measured bias — definitions are negotiated, not derived from data.
• corroborated: 2 independent passages support this claim — Joseph Avery, Jim Sidanius, Joel Cooper, Gregory Davis, Amanda N., Bias in the Law: A Definitive Look at…, 1182