An Artificial Intelligence algorithm trained on data that reflect racial biases may yield racially biased outputs, even if the algorithm on its own is unbiased. For example, algorithms used to schedule medical appointments in the USA predict that Black patients are at a higher risk of no-show than non-Black patients, though technically accurate given existing data that prediction results in Black patients being overwhelmingly scheduled in appointment slots that cause longer wait times than non-Black patients. This perpetuates racial inequity, in (...) this case lesser access to medical care. This gives rise to one type of Accuracy-Fairness trade-off: preserve the efficiency offered by using AI to schedule appointments or discard that efficiency in order to avoid perpetuating ethno-racial disparities. Similar trade-offs arise in a range of AI applications including others in medicine, as well as in education, judicial systems, and public security, among others. This article presents a framework for addressing such trade-offs where Machine Learning and Optimization components of the algorithm are decoupled. Applied to medical appointment scheduling, our framework articulates four approaches intervening in different ways on different components of the algorithm. Each yields specific results, in one case preserving accuracy comparable to the current state-of-the-art while eliminating the disparity. (shrink)

I critically examine the eliminativist theories of race or racism, and the behavioral theory of racism, which provide the theoretical foundation, respectively, for the nominalist and substantive conceptualizations of the idea of a post-racial era. The eliminativist theories seek to eliminate the concepts of “race” or “racism” from our discourse. Such elimination indicates a nominalist sense of the idea of a post-racial era. The behavioral theory of racism argues that racism must be manifested in obviously harmful actions. And because such (...) harmful actions are not prevalent today, this implies that we are in a post-racial era in a substantive sense. I conceptualize some subtle forms of racism that are prevalent today, which cannot be captured by the behavioral theory, but can best be captured by doxastic theories of racism. I conceptualize a substantive idea of a post-racial era, and then argue based on such conceptualization, that we are not in a post-racial era because subtle forms of racism are still prevalent today. (shrink)