Beyond Bias and Discrimination: Redefining the AI Ethics Principle of Fairness in Healthcare ML Algorithms

The increasing implementation of ML algorithms in healthcare has made the need for fairness in healthcare ML algorithms (HMLA) a very urgent task. However, while the debate on fairness in the ethics of AI has grown significantly in the last decade, the concept of fairness as an ethical value has not yet been sufficiently explored thus far. This paper draws on moral philosophy to fill this gap. It shows how an ethical inquiry into the concept of fairness helps highlight shortcomings in the current conceptualization of fairness in HMLA and better redefine the AI ethics principle of fairness to design fairer HMLA.