Geiger studies the relationships between science, technology, and society — not only how science and technology have substantial impacts on society, but also how they are social institutions in themselves. He studies issues of fairness, accountability, transparency, responsibility, and contestability in machine learning, particularly in online content moderation. He has examined how values and biases are embedded in these technologies and how communities make decisions about how to use or not use them. Geiger also studies the development of data science as an academic and professional field, as well as the sustainability of free/open-source software and scientific cyberinfrastructure projects.
Geiger earned his Ph.D in 2015 at the UC Berkeley School of Information and the Berkeley Center for New Media, then was the staff ethnographer at the UC Berkeley Institute for Data Science. He joined UCSD in 2020, jointly appointed as faculty in the Department of Communication. Geiger is a methodological and disciplinary pluralist who collaborates across many different ways of knowing, but his work is often grounded in the fields of communication & media studies, science & technology studies, cultural anthropology, organizational sociology, human-computer interaction, and history and philosophy of science.