Research agenda

Computational Community Design.

How can communities understand, design, and change the social and informational systems shaping their lives?


An agenda for
collective possibility.

Read the agenda

We study the connections between personal agency, relationships, and the structures of collective life. Our agenda brings theoretical inquiry into conversation with models, computational instruments, and experiments.

01 / Perspective

Personal intelligence

A person’s representations, knowledge, and memory—and their ability to understand and control them.

How can people understand and direct their own lives?

02 / Perspective

Ambient social intelligence

The capacity to recognize relevant circumstances and help members of a group discover opportunities to support one another.

What can a group understand about itself?

03 / Perspective

Social system design

The roles, rules, norms, and information flows that shape how people relate, coordinate, and participate.

How can people shape the conditions of collective life?

These perspectives can be studied independently or together. Their shared concern is human relationships, agency, and collective outcomes.

Explore our methods
Intellectual territory

Seven areas of inquiry.

01

Information environments

How information shapes perception, judgment, and the possibilities people can see.

02

Agency & self-direction

How people gain meaningful control over their choices and participation in social systems.

03

Identity & representation

How digital representations influence the ways people are understood by others and institutions.

04

Communities & institutions

How roles, norms, and shared structures shape relationships and collective life.

05

Coordination & collective intelligence

How people discover opportunities, share knowledge, and organize action together.

06

AI-mediated social systems

How intelligent technologies change communication, trust, authority, and human relationships.

07

Adaptive & life-giving systems

How social and technological systems learn from their effects and evolve with their members.