Caresets and the Experimental Public Co-Design of Tomorrow

Abstract

Participatory planning can help cities make better policy and planning decisions. An effective participatory planning framework must represent complex urban systems (compositional), compute Pareto-optimal solutions (computational), and incorporate residents into the decision-making process (collaborative).

We build a mathematical language using partially ordered sets to formally describe care in three forms: preference, ethics, and design. We then create a compositional, computational, and collaborative framework for participatory planning called the Experimental Public Co-Design of Tomorrow (EPCODOT). This framework adapts monotone co-design to work with our language of care and extends the approach with a collaborative interface. We demonstrate EPCODOT's capabilities first by modeling an MIT Senseable City Lab research project on trade-offs between data privacy and urban well-being, and then by modeling its potential application with a real public project in Durham, North Carolina. We provide a software prototype at epcodot.com.

This work develops two interconnected contributions: a mathematical language of care connecting applied category theory, decision theory, and ethics; and EPCODOT, a software tool enabling participatory planning for researchers, communities, and cities. Future work should pursue four directions: exploring additional category-theoretic structures within the mathematical language, formalizing connections to social choice and decision theory, testing EPCODOT directly with communities, and enhancing the computational capabilities of the framework's monotone co-design adaptation.