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| Natura: | Preprint |
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2024
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| Accesso online: | https://arxiv.org/abs/2412.09988 |
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| _version_ | 1866912154590904320 |
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| author | 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 |
| author_facet | 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 |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_09988 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | AI and the Future of Digital Public Squares 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 Computers and Society Artificial Intelligence 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. |
| title | AI and the Future of Digital Public Squares |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2412.09988 |