Application of fairness to healthcare, organizational justice, and finance: A survey

While artificial intelligence is widely employed in many applications, it is vulnerable to bias and unethical use. Therefore, fairness evaluation tools and bias mitigation algorithms have drawn considerable attention. The main concern arises when an intelligent system is developed to make life-changing decisions in a social application. The ethical aspects of the decisions are vital because they significantly affect human lives. Therefore, numerous techniques have been developed to prevent discrimination in the learning algorithm output. This survey paper focuses on the application of fairness techniques in healthcare, organizational justice, and finance. Different kinds of discrimination are identified and comprehensively discussed in each application, and state-of-the-art fairness methods in each category are reviewed.