Values of fairness, antidiscrimination, and inclusion occupy a central place in the emerging ethics of data and algorithms. Their importance is underscored by the reality that data-intensive, algorithmically-mediated decision systems—as represented by artificial intelligence and machine learning (AI/ML)—can exacerbate existing (or generate new) injustices, worsening already problematic distributions of rights, opportunities, and wealth. At the same time, critics of certain “fair” or “inclusive” approaches to the design and implementation of these systems have illustrated their limits...