ABSTRACT
“That’s not fair” is a common refrain, whether complaining about a rule being enforced at work or that a sister got a larger ice cream cone. However, explaining why an act is not fair is quite nuanced. Definitions of justice and fairness are important for the ethics of data analytics because many times the programs are designed to allocate “things” or “goods,” to use the term of justice scholars. We care how goods like admittance to college, health care, bonuses, sentences, and even ice cream are allocated whether by the government or by a company or by our parents. The chapter summary explains why relying on mathematically convenient definitions of fairness does not address all questions of fairness. The readings explore three different approaches to fairness and justice in philosophy, where each has a different answer to what does it mean to be fair and just? Readings include John Rawls and his theory of justice focused on liberty and the least fortunate, Robert Nozick with a focus on acquisition and transfer of goods, and Michael Walzer and an excerpt from his ideas on spheres of justice. The related cases are (1) the COMPAS sentencing algorithm, and (2) the use of predictive analytics in universities.
