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.

Novelli, C., Argota Sánchez-Vaquerizo, J., Helbing, D., Rotolo, A., Floridi, L. (2025). A replica for our democracies? On using digital twins to enhance deliberative democracy. AI & SOCIETY, 2025, 1-19 [10.1007/s00146-025-02511-7].

A replica for our democracies? On using digital twins to enhance deliberative democracy

Rotolo, Antonino
;
Floridi, Luciano
2025

Abstract

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.
2025
Novelli, C., Argota Sánchez-Vaquerizo, J., Helbing, D., Rotolo, A., Floridi, L. (2025). A replica for our democracies? On using digital twins to enhance deliberative democracy. AI & SOCIETY, 2025, 1-19 [10.1007/s00146-025-02511-7].
Novelli, Claudio; Argota Sánchez-Vaquerizo, Javier; Helbing, Dirk; Rotolo, Antonino; Floridi, Luciano
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1048799
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