FairTargetSim: An Interactive Simulator for Understanding and Explaining the Fairness Effects of Target Variable Definition

Machine learning requires defining one's target variable for predictions or decisions, a process that can have profound implications on fairness: biases are often encoded in target variable definition itself, before any data collection or training. We present an interactive simulator, FairTargetSim (FTS), that illustrates how target variable definition impacts fairness. FTS is a valuable tool for algorithm developers, researchers, and non-technical stakeholders. FTS uses a case study of algorithmic hiring, using real-world data and user-defined target variables. FTS is open-source and available at: http://tinyurl.com/ftsinterface. The video accompanying this paper is here: http://tinyurl.com/ijcaifts.

AI Fairness: from Principles to Practice

This paper summarizes and evaluates various approaches, methods, and techniques for pursuing fairness in artificial intelligence (AI) systems. It examines the merits and shortcomings of these measures and proposes practical guidelines for defining, measuring, and preventing bias in AI. In particular, it cautions against some of the simplistic, yet common, methods for evaluating bias in AI systems, and offers more sophisticated and effective alternatives. The paper also addresses widespread controversies and confusions in the field by providing a common language among different stakeholders of high-impact AI systems. It describes various trade-offs involving AI fairness, and provides practical recommendations for balancing them. It offers techniques for evaluating the costs and benefits of fairness targets, and defines the role of human judgment in setting these targets. This paper provides discussions and guidelines for AI practitioners, organization leaders, and policymakers, as well as various links to additional materials for a more technical audience. Numerous real-world examples are provided to clarify the concepts, challenges, and recommendations from a practical perspective.