ES138: Computing, Spatial Design, and Human Values

Description

Is design a unique computational domain? What is the relationship of rule-based to data-driven viewpoints of computing in design? Can computing, whether with rules or with data, assimilate design values related to aesthetics, utility, or other? Are the design disciplines an integral element in the pursuit for general intelligent systems?

ES138 is research-oriented course that explores answers to these various questions from the point of view of computing paradigms that have had major influence on computational thinking in spatial design disciplines: visual calculating for rule-based generative design and artificial intelligence models for problem-solving and learning. Focuses on building technical and hands-on experience with rule-based and data-driven viewpoints of computing in design, and a critical understanding of their capabilities and limitations for spatial thinking and expression or for assimilating value judgments related to aesthetics, utility, or other. Integrates relevant ideas and approaches from design theory, art, mathematics, architecture, aesthetics, linguistics, cognitive science, computer science, and artificial intelligence to foster a critical (evaluative) mindset on computing concepts relevant for both thinking about and doing design. Students develop an independent research oriented project that embodies the themes of the course.

Recommended Background and Prerequisites There is no formal prerequisite for this course, but enrollment is limited. Students with an interest in any area of design are welcome to complete an enrollment application survey in the beginning of the semester. If the course is oversubscribed, preference will be given to students who have taken an introductory course combining computation, art, or design (e.g., ES50/51, CS73, CS79) as well as students pursuing joint concentrations (e.g., computer science, art and architecture, engineering, cognitive science).

Enrollment is limited and students are required to complete an enrollment application

Note: Graduate students enrolled in a master's or PhD program will be accepted on a limited basis.

Instructor and Course Assistants

Alexandros Haridis (Instructor)
Email: haridis@seas.harvard.edu
Office Hours: Fridays 3pm-6pm, in SEC LL1.214(room/hours subject to change)

Course Assistants (Spring'24)

Joachim Asare (Teaching Fellow) - joachimasare@mde.harvard.edu
Katarina Richter-Lunn (Research Assistant) - krichterlunn@gsd.harvard.edu

Course Sessions

Class meetings:
Tuesdays and Thursdays 12:45pm to 2:00pm, in SEC Room 1.316

Materials and Access:
All course materials and assignments including excerpts from readings will be provided through Canvas. There is no standard textbook for this course. Primary reference materials and prepared course materials and case studies will be provided.

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