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. MIT Architecture alumnus and researcher Alexandros Haridis explores the history of computational aesthetics in "Beyond Data-Driven Aesthetics," a Keller Gallery exhibition that translates algorithms, machine learning systems, and theories of aesthetic judgment into physical installations and interactive visualizations.
Key Takeaways
- School of Architecture and Planning Publication Date : June 29, 2026 Press Inquiries Press Contact : Adelaide Zollinger Email: mitmad@mit.
- Each theme offers a window into a distinct computational approach to aesthetic judgment, drawing on ideas developed in influential books and research papers.
- A: The conceptual origins of "Beyond Data-Driven Aesthetics" emerged from three intersecting lines of research.
- For example, in the 1956 Dartmouth Summer Research Project, a foundational event for the field of AI, creation and evaluation processes were identified as one of seven key dimensions of human intelligence that future AI research should address.
Second, the exhibition was influenced by research in design computation and shape grammars that investigates relationships between human insight and computation through rule-based methods, rather than purely data-driven learning.
- Finally, the exhibition was motivated by the use of design, fabrication, and data visualization as methods for interpreting mathematical concepts, algorithms, and "black box" machine-learning systems.
MIT Architecture alumnus and researcher Alexandros Haridis explores the history of computational aesthetics in "Beyond Data-Driven Aesthetics," a Keller Gallery exhibition that translates algorithms, machine learning systems, and theories of aesthetic judgment into physical installations and interactive visualizations. 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. School of Architecture and Planning Publication Date : June 29, 2026 Press Inquiries Press Contact : Adelaide Zollinger Email: mitmad@mit.
edu MIT Morningside Academy for Design : "Beyond Data-Driven Aesthetics," by Alexandros Haridis at the MIT Keller Gallery, presents historical and contemporary works that examine how algorithms, computation, and machine learning have shaped aesthetic thinking in architecture and design. Credits : Photo: Qingyang Xie Caption : The exhibition is organized around five thematic areas - Aesthetic Measure, Aesthetic Guidelines, Algorithmic Aesthetics, Aesthetic Appropriation, and Aesthetic Novelty. Each theme offers a window into a distinct computational approach to aesthetic judgment, drawing on ideas developed in influential books and research papers.
Credits : Photo: Adrian Yu Previous image Next image "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?
For more details please read the original article at MIT News AI.
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