Michael Hoye is a media scholar and artist examining the material practices that construct the latent spaces found within deep learning systems. His work combines hands-on model training with critical theory to investigate how AI embeds ideological frameworks and restructures cultural production.
He holds an MA in Media Studies from San Francisco State University and was a Research Fellow at SF State’s Science, Technology, and Society Research Hub in 2024-25. His thesis “Deep Learning as a Symbolic Form” explored how deep learning systems impose representational logic on cultural materials. Recent work includes “Deepfakes as Myth and the Aestheticization of State Violence,” presented at the Ethics and Aesthetics of Artificial Images conference in Venice, Italy (forthcoming publication), and “Exploration as Critique: Critical AI Studies,” presented at AEJMC 2025.
Before returning to academia in 2018, Michael worked as a professional musician with Atlantic and Elektra Records—a trajectory that informs his research on how computational systems restructure creative labor.
Michael Hoye 