Document Type
Report
Publication Date
9-3-2024
Language
en-US
Abstract
Cities globally have begun experimenting with using generative artificial intelligence (Gen AI) for civic engagement. Civic engagement is essential to a well-functioning government and involves the various interactions between the public and the city to share information and make decisions. Using Gen AI for civic engagement holds much potential, including the deployment of chatbots, language translation, synthesis of complex and technical documents, visioning and co-creation of design ideas, data visualization, and simulation and scenario planning. However, with these opportunities comes numerous concerns for the accuracy of results, algorithmic bias, private sector involvement, digital equity, and environmental costs. Our review of emerging projects combined with data from conversations with city officials illustrates the importance of human oversight and contextualization when working with Gen AI for civic engagement. Without this oversight, inaccurate results might be mistaken for fact, and the biases inherent in large language models (LLMs) might reinforce dominant culture narratives—the outcomes of which would surely erode public trust. Given these risks, we argue that the successful integration of Gen AI for civic engagement must be powered by people who use their judgment to validate outputs, mitigate potential errors, contextualize results, and build trust between the government and the community. This people-centered approach requires developing methods to involve communities in decisions about how AI tools should shape city–resident interactions and the design of guidelines for how Gen AI can be used responsibly and ethically for civic engagement.
Recommended Citation
Sarah Williams, Sara Beery, Chris Conley, Michael L. Evans, Santiago Garces, Eric Gordon, Nigel Jacob & Eden Medina,
People-Powered Gen AI: Collaborating with Generative AI for Civic Engagement
(2024).
Available at:
https://doi.org/https://doi.org/10.21428/e4baedd9.f78710e6
