A New Research Agenda for AI and Civic Engagement

A new paper lays out a research agenda for further developing the use of large language models to create more deliberative and healthier digital public squares.

Dane Gambrell

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Last month, more than two dozen experts published a position paper about the role of AI-enabled technologies in fostering civic engagement. Authored by researchers, practitioners and technologists from the government, nonprofit, and technology sectors, the paper explores how emerging technologies are transforming how we engage with one another in the digital public square. The paper argues in favor of more research and experimentation to support the use of large language models in creating more deliberative and healthier digital public spaces.

Abstract: Two substantial technological advances have reshaped the public square in recent decades: first with the advent of the internet and second with the recent introduction of large language models (LLMs). LLMs offer opportunities for a paradigm shift towards more decentralized, participatory online spaces that can be used to facilitate deliberative dialogues at scale, but also create risks of exacerbating societal schisms. Here, we explore four applications of LLMs to improve digital public squares: collective dialogue systems, bridging systems, community moderation, and proof-of-humanity systems. Building on the input from over 70 civil society experts and technologists, we argue that LLMs both afford promising opportunities to shift the paradigm for conversations at scale and pose distinct risks for digital public squares. We lay out an agenda for future research and investments in AI that will strengthen digital public squares and safeguard against potential misuses of AI.

One of the examples highlighted in the paper is the New Jersey AI Task Force’s use of Policy Synth to develop policy solutions to the problem of AI-driven disruptions to the state’s economy and workforce. Developed by The GovLab and Citizens Foundation, Policy Synth is an open source toolkit that uses AI agents to synthesize the findings from large-scale engagement together with findings from research to develop evidence-based policies. 

Read the full position paper here

Shorter summaries of the paper are available here and here

 

Cover photo: A public square in Bologna, Italy, by Maria Bobrova via Unsplash.com.

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