Avital Meshi is a new media artist who focuses on performance and AI technology. In her work, she examines the influence of AI on our behavior and on our social environment. She invites viewers to intermingle with the technology and find out how they are seen through its lens. Inspired by ideas from new and relational aesthetics, her goal is to allow viewers to reveal their own power to act upon technology. Meshi holds an MFA in Digital Arts and New Media from UC Santa Cruz and a BFA from the School of the Art Institute of Chicago. She will begin her PhD studies in performance studies at UC Davis this coming fall. Meshi also holds a BSc and an MSc in behavioral biology from the Hebrew University of Jerusalem, Israel.
The work “Deconstructing Whiteness” by Avital Meshi naively inquires what makes the machine identify whiteness. To do this, the artist uses the principle of reverse engineering – examining a technical object or process from the outside through the results that various inputs provide. The artist performs racial stereotypes in front of a face classification algorithm in an attempt to decode the biases originally encoded in the training set. In the context of the augmented reality app, it becomes clear that visualizations like the green squares are themselves already a form of augmented reality and augmented perception of the world.
“Deconstructing Whiteness” documents an interactive AI performance. The piece examines the visibility of race in general, and ‘Whiteness’ in particular – through the lens of AI technology. The artist uses an off-the-shelf facial recognition model to examine her own racialized visibility. Drawing on performative behavior to change her facial expressions and hairstyle, she manages to modify the confidence level by which the machine recognizes her as ‘White.’ “Deconstructing Whiteness” reveals the underlying racial constructs that inform the technological visualization of race. The poster contains nine panels. Each of these can be activated individually to have the performance come to life. This allows viewers to become involved in this thorough self-examination and the relentless quest for any encoded bias.
