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14109 : Machine Learning at the Archive

Description: In “An Archival Impulse,” Hal Foster describes the archive as “found yet constructed, factual yet fictive, public yet private." This is a hybrid seminar / workshop course that brings together making, researching and collecting with the goal of expanding the discourse around archives to address machine learning. Foster's set of tangled binaries provide a foundation on which to build a formal and critical inquiry into the procedural, technological and institutional pressures involved in working with machine learning, particularly as an individual researcher or artist. Topics include: How do the datasets used for machine learning correspond to or differ from traditional physical archives? How does the speculative discourse around the potential for artificial intelligence inform data collection and usage? How has the archive's problematic history of informing and feeding on various "-isms" translated to the digital age and how do we respond to that situation? How can art be used to investigate or interfere with all of the above?

Instructor(s): Cameron Mankin

Offered: Winter 2022

Category: Theory

Cluster(s): Creative Computing