Machine learning threatens or promises to upend many industries. The goal of this seminar is to have students develop a sense of literacy around machine learning, its promises, pitfalls, and possibilities. This seminar will investigate how machine learning intersects with art and design processes, emphasizing the role of decision-making between human and machine. Applications of ML in art and architecture will be explored through a series of case studies with an emphasis on the potential of ML as collaborator. During these case studies, students will also consider the second order impacts and ethical ramifications. Students will eventually isolate a moment form their own design process and expand on it by developing a machine learning algorithm of their own accompanied by a five page paper.

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Spring 2021
The Mechanical Artifact: Ultra Space
Dana Karwas, Ariel Ekblaw