The question of how to govern well has been a central topic of inquiry in both political science and philosophy. We contribute to this discourse by examining the epistemic foundations of good governance within democratic and autocratic systems. Drawing on the existing debate surrounding the epistemic justification of democratic procedures (Estlund, 2000; Goodin & Spiekermann, 2018; Landemore, 2012), we construct a thought experiment where agents are tasked with collectively identifying some optimal collective decision. We hypothesize that, for such tasks, democratic decision making systems possess an institutionally driven epistemic advantage compared to autocratic ones. To explore this hypothesis, we develop a simulation where a group of agents sets out to estimate the optimal level of public good provision. To this end, group members engage in individual learning, collective deliberation and voting. We then assess and compare two distinct mechanisms for aggregating individual estimates to the group level: one reflecting a democratic process and the other an autocratic setting. Our findings reveal three key insights. First, democratic decision-making outperforms autocratic methods in terms of judgment accuracy. Second, democratic decision-making processes turn out to fare best when individual citizens are not impartial but instead employ a mild bias towards their own needs when assessing the optimal level of public good supply. A last finding is that, under certain conditions, restricting the duration of deliberation can enhance the epistemic precision of collective decisions.
LLMs are increasingly deployed in settings that require collective reasoning on complex, value-laden problems. Confidence in these deployments rests largely on benchmarks for verifiable tasks (mathematics, coding, coordination games), yet many of these applications concern problems where no objectively correct answer e...
Maurice Flechtner· Proceedings of the AAAI/ACM...· 0 citations
Public reasoning, a manner of democratic deliberation that can generate meaningful conceptions of justice, the collective good, and other unifying political values among individuals subscribing to varied and contrasting doctrines, has been a perennial concern among political philosophers from historical thinkers such a...
This Article argues that legitimacy is an autonomous regulatory objective, distinct from alignment and not secured by it, which seats consequential AI rule-setting in venues a polity already treats as authoritative.
It is argued that many of the ways in which computer scientists, deliberative democratic practitioners, and others are using LLMs to do this threatens the non-instrumental value of a collective's ability to determine its own future.
Lorenzo Manuali· Philosophy & Technology· 0 citations
A framework and research agenda is developed for identifying when AI supports autonomous citizenship, when it substitutes for citizens’ judgment or agency, and why the same systems produce different outcomes across political tasks depending on how citizens use them.
C. Anderson, Elena Pro· Perspectives on Politics· 0 citations
Society constantly has to determine the boundaries of what it deems acceptable, from legislative decisions to the guardrails governing autonomous systems. We initiate the axiomatic study of collective consent: given individuals'attitudes toward options, which options should receive societal consent? We organize our ana...
Chris Dong, Sonja Kraiczy, Rohit Vasishta et al.· 0 citations
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