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This exhibition investigates the historical lineage of aesthetic judgment in computing, contrasting modern data-driven machine learning models like Stable Diffusion with earlier rule-based design computation methods. By translating algorithms into physical installations, it contextualizes current AI debates about creativity within a broader 20th-century intellectual framework that predates today's generative boom.
3 Questions: Beyond data-driven aesthetics
In a new Keller Gallery exhibition, Alexandros Haridis SM ’17, PhD ’22 traces centuries of ideas about aesthetic judgment and explores how design can make complex computational systems visible.
“Beyond Data-Driven Aesthetics,” by MIT Architecture alumnus and researcher Alexandros Haridis, on view at the MIT Keller Gallery through June 30, examines 20th- and 21st-century efforts to transform computing into a medium for creative production and aesthetic judgment in architecture and the applied arts. Drawing on philosophy, mathematics, computer science, and design computation, the exhibition translates algorithms, theories, and machine-learning systems into physical installations and interactive visualizations. Q: What inspired “Beyond Data-Driven Aesthetics,” and what questions does it explore? A: The conceptual origins of “Beyond Data-Driven Aesthetics” emerged from three intersecting…
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