A Replica for our Democracies? On Using Digital Twins to Enhance Deliberative Democracy

Novelli, Claudio, Sánchez-Vaquerizo, Javier Argota, Helbing, Dirk, Rotolo, Antonino, Floridi, Luciano

arXiv.org Artificial Intelligence 

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 suggest s where future research should focus .

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