Attempts at Invading Machine Learning Systems, Installation, 2021

The instrumentalization of biometric data orchestrated through surveillance technologies can press today’s users of communication tools, devices, and platforms to opt out of such systems. This graduate research thesis aims to reveal the imperceptible forces that underwrite recognition technologies, through a series of experiments and the creation of multimedia installations that address the unethical relationship between active users and structures of control. Initiated at Emily Carr University, Vancouver, from September 2020 to May 2022, this research project hopes to uncover new possibilities for machine learning systems to propose protective devices based on image datasets composed of theatrical masks. This project explores the potential to apply generative models simultaneously as a response to facial recognition technology and as a mode of resistance to the dominance of these models. Finally, this research contributes to raising awareness toward extractive systems and surveillance technologies, while questioning the impact of artificial intelligence and its potential future outcomes.