Can AI mediation improve democratic deliberation?
Fuente:
arXiv
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| Auteurs principaux: | , , , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866912812079513600 |
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| author | Tessler, Michael Henry Evans, Georgina Bakker, Michiel A. Gabriel, Iason Bridgers, Sophie Jain, Rishub Koster, Raphael Rieser, Verena Dragan, Anca Botvinick, Matthew Summerfield, Christopher |
| author_facet | Tessler, Michael Henry Evans, Georgina Bakker, Michiel A. Gabriel, Iason Bridgers, Sophie Jain, Rishub Koster, Raphael Rieser, Verena Dragan, Anca Botvinick, Matthew Summerfield, Christopher |
| contents | The strength of democracy lies in the free and equal exchange of diverse viewpoints. Living up to this ideal at scale faces inherent tensions: broad participation, meaningful deliberation, and political equality often trade off with one another (Fishkin, 2011). We ask whether and how artificial intelligence (AI) could help navigate this "trilemma" by engaging with a recent example of a large language model (LLM)-based system designed to help people with diverse viewpoints find common ground (Tessler, Bakker, et al., 2024). Here, we explore the implications of the introduction of LLMs into deliberation augmentation tools, examining their potential to enhance participation through scalability, improve political equality via fair mediation, and foster meaningful deliberation by, for example, surfacing trustworthy information. We also point to key challenges that remain. Ultimately, a range of empirical, technical, and theoretical advancements are needed to fully realize the promise of AI-mediated deliberation for enhancing citizen engagement and strengthening democratic deliberation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_05904 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Can AI mediation improve democratic deliberation? Tessler, Michael Henry Evans, Georgina Bakker, Michiel A. Gabriel, Iason Bridgers, Sophie Jain, Rishub Koster, Raphael Rieser, Verena Dragan, Anca Botvinick, Matthew Summerfield, Christopher Computers and Society Artificial Intelligence The strength of democracy lies in the free and equal exchange of diverse viewpoints. Living up to this ideal at scale faces inherent tensions: broad participation, meaningful deliberation, and political equality often trade off with one another (Fishkin, 2011). We ask whether and how artificial intelligence (AI) could help navigate this "trilemma" by engaging with a recent example of a large language model (LLM)-based system designed to help people with diverse viewpoints find common ground (Tessler, Bakker, et al., 2024). Here, we explore the implications of the introduction of LLMs into deliberation augmentation tools, examining their potential to enhance participation through scalability, improve political equality via fair mediation, and foster meaningful deliberation by, for example, surfacing trustworthy information. We also point to key challenges that remain. Ultimately, a range of empirical, technical, and theoretical advancements are needed to fully realize the promise of AI-mediated deliberation for enhancing citizen engagement and strengthening democratic deliberation. |
| title | Can AI mediation improve democratic deliberation? |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2601.05904 |