A Replica for our Democracies? On Using Digital Twins to Enhance Deliberative Democracy
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Abstract (arXiv)
Deliberative democracy depends on carefully designed institutional frameworks, such as participant selection, facilitation methods, and decision-making mechanisms, that shape how deliberation performs. However, identifying optimal institutional designs for specific contexts remains challenging when relying solely on real-world observations or laboratory experiments: they can be expensive, ethically and methodologically tricky, or too limited in scale to give us clear answers. Computational experiments offer a complementary approach, enabling researchers to conduct large-scale investigations while systematically analyzing complex dynamics, emergent and unexpected collective behavior, and risks or opportunities associated with novel democratic designs. Therefore, this paper explores Digital Twin (DT) technology as a computational testing ground for deliberative systems (with potential applicability to broader institutional analysis). By constructing dynamic models that simulate real-world deliberation, DTs allow researchers and policymakers to rigorously test "what-if" scenarios across diverse institutional configurations in a controlled virtual environment. This approach facilitates evidence-based assessment of novel designs using synthetically generated data, bypassing the constraints of real-world or lab-based experimentation, and without societal disruption. The paper also discusses the limitations of this new methodological approach and suggests where future research should focus.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Apr 2025.
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Citing papers per year: 2025: 2; 2026: 2.
4 papers.
- 2025Prompt Injection Vulnerability of Consensus Generating Applications in Digital Democracycited by 2
- 2025Aligning Trustworthy AI with Democracy: A Dual Taxonomy of Opportunities and Riskscited by 0
- 2026Beyond the Townhall: Spatial Anchoring and LLM Agents for Scalable Participatory Urban Planningcited by 0
- 2026What is Left for Us? Second Scholarship Against the Degradation of Research by AIcited by 0
- 2026What is Left for Us? Second Scholarship Against the Degradation of Research by AI4 Jul 2026
- 2026Beyond the Townhall: Spatial Anchoring and LLM Agents for Scalable Participatory Urban Planning16 Mar 2026
- 2025Prompt Injection Vulnerability of Consensus Generating Applications in Digital Democracy6 Aug 2025
- 2025Aligning Trustworthy AI with Democracy: A Dual Taxonomy of Opportunities and Risks19 May 2025