AI Presents Both Problems and Opportunities for Minorities

Abstract The recent Point article by Wu (2026) calls for a better understanding of factors that could lead to the development of AI systems that are likely to perpetuate social inequality. The Point article introduces the idea that computational beliefs interact with computational inequalities in a more systematic manner that develops AI systems which perpetuate biases. We present our counterpoint and show where we agree with Wu (2026) but also present areas that are not accounted for in the Point article. Specifically, using cases from financial services and HR systems, we highlight how algorithmic transparency driven by organizational governance and regulatory intervention can mitigate many of the issues, leading to the development of AI systems that could potentially be bias free.