The Myth of Algorithmic Justice: Why Rawlsian Frameworks Can’t Fix Our Algorithms with Aaron Schultz

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Algorithms play an important role across a wide range of social domains. They are deployed by the criminal justice system, the health care system, educational institutions, and employers. They also significantly shape the information we consume, from news and social media to entertainment. Given the scope of their influence, it is crucial that the algorithms impacting our lives operate fairly. While efforts to ensure algorithmic fairness are widespread, we must also recognize the theoretical limits of these approaches. This talk examines those boundaries by exploring the challenges of applying John Rawls’s conception of fairness to modern algorithms.

Aaron Schultz is an Assistant Professor in the Department of Philosophy at Michigan State University. His research investigates the ethical, political, and social implications of emerging technology, with a focus on AI governance, algorithmic fairness, and the protection of attentional freedom. Drawing on a background in political and Buddhist philosophy, he teaches courses spanning the philosophy of technology, propaganda and justice, health care ethics, and Buddhist thought.

Aaron earned his Ph.D. from Binghamton University in 2021. Beyond his work at MSU, he brings his critical perspective to public and policy domains, serving as a research contributor for the Center for AI and Digital Policy’s Artificial Intelligence and Democratic Values Report 2025 and regularly writing for The Prindle Post.