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Improving human collective decision-making through animal and artificial intelligenceuse asterix (*) to get italics
Cédric Sueur, Christophe Bousquet, Romain Espinosa and Jean-Louis DeneubourgPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"
<p style="text-align: justify;">Whilst fundamental to human societies, collective decision-making such as voting systems can lead to non-efficient decisions, as past climate policies demonstrate. Current systems are harshly criticized for the way they consider voters’ needs and knowledge. Collective decision-making is central in human societies but also occurs in animal groups mostly when animals need to choose when and where to move. In these societies, animals balance between the needs of the group members and their own needs and rely on each individual’s (partial) knowledge. We argue that non-human animals and humans share similar collective decision processes, among which are agenda-setting, deliberation and voting. Recent works in artificial intelligence have sought to improve decision-making in human groups, sometimes inspired by animals’ decision-making systems. We discuss here how our societies could benefit from recent advances in ethology and artificial intelligence to improve our collective decision-making system.</p> should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https://
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collective decisions, vote, democracy, representativeness, machine learning
NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).
Animal networks, Political networks
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2021-04-19 07:10:05
Frédéric Amblard