Description

How and why the current public engagement model has run its course--and how AI-assisted listening at scale can help.

We often assume that citizen participation is the biggest barrier to effective representation. In fact, governments are sitting on mountains of civic data that they cannot effectively process.

In How Institutions Listen, Eric Gordon shows how we can marshal this wealth of data with human-centered AI--making sense of the available civic data, acting upon it, and, in turn, restoring public trust.

Bridging theory and practice, the book introduces the concept of "listening at scale"--an institutional capacity to listen, which means to not only gather input, but to discern, respond, and evolve in dialogue with the public. It tracks trends in digital governance, from open data to civic tech dashboards, and critiques how contemporary tools can harm communities by reducing their participation to data extraction.

Through richly researched case studies--from city governments deploying sentiment analysis to community-centered design efforts--the book shows how listening is being reshaped by digital infrastructures, and how those infrastructures, in turn, reshape the meaning of voice and representation. Rather than promoting more apps or surveys, the author urges a reorientation: designing institutions that can engage with complexity, ambiguity, and dissent without defaulting to control.