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AI and the Future of Digital Public Squares

Authors :
Goldberg, Beth
Acosta-Navas, Diana
Bakker, Michiel
Beacock, Ian
Botvinick, Matt
Buch, Prateek
DiResta, Renée
Donthi, Nandika
Fast, Nathanael
Iyer, Ravi
Jalan, Zaria
Konya, Andrew
Danciu, Grace Kwak
Landemore, Hélène
Marwick, Alice
Miller, Carl
Ovadya, Aviv
Saltz, Emily
Schirch, Lisa
Shalom, Dalit
Siddarth, Divya
Sieker, Felix
Small, Christopher
Stray, Jonathan
Tang, Audrey
Tessler, Michael Henry
Zhang, Amy
Publication Year :
2024

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.<br />Comment: 40 pages, 5 figures

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2412.09988
Document Type :
Working Paper