Towards Practical Software Discrimination Testing

Technological advancements over the years have led to increasingly complex software systems. The recent surge in artificial intelligence (AI) has, while reducing human effort, further contributed to this complexity. Among the growing concerns in this domain are the ethical implications of developing and using such systems. Regardless of whether a system explicitly incorporates AI, underlying software infrastructures have demonstrated instances of discriminatory behavior, resulting in undesired outcomes. To address this challenge, my research focuses on discrimination testing as a means to ensure equitable behavior in software systems. As part of this effort, I plan to build on insights from my earlier work, which involved compiling a list of existing tools and user studies on their effectiveness. My goal is to design a more explainable and generalizable discrimination testing tool that can be applied across various systems.