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Prevailing top-down systems in politics and economics struggle to keep pace with the pressing challenges of the 21st century, such as climate change, social inequality and conflict. Bottom-up democratization and participatory approaches in politics and economics are increasingly seen as promising alternatives to confront and overcome these issues, often with ‘utopian’ overtones, as proponents believe they may dramatically reshape political, social and ecological futures for the better and in contrast to contemporary authoritarian tendencies across various countries. Institutional specifics and the associated collective human behavior or culture remains little understood and debated, however. In this article, I propose a novel research agenda focusing on ‘utopian’ democratization efforts with formal and computational methods as well as with artificial intelligence – I call this agenda ‘Artificial Utopia’. Artificial Utopias provide safe testing grounds for new political ideas and economic policies ‘in-silico’ with reduced risk of negative consequences as compared to testing ideas in real-world contexts. An increasing number of advanced simulation and intelligence methods, that aim at representing human cognition and collective decision-making in more realistic ways, could benefit this process. This includes agent-based modeling, reinforcement learning, large language models and more. I clarify what some of these simulation approaches can contribute to the study of Artificial Utopias with the help of two institutional examples; the citizen assembly and the democratic firm. Finally, I discuss open questions and future research directions related to the broader Artificial Utopia agenda. • Introduces Artificial Utopia to explore alternative democratic futures. • Uses simulation and AI to tackle democratic institutional challenges. • Maps simulations onto citizen assemblies and democratic firm challenges. • Identifies open questions and methodological gaps in Artificial Utopia.
Yannick Oswald (Wed,) studied this question.