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Section: Network Science
Topic: Sociology, Political sciences

Improving human collective decision-making through animal and artificial intelligence

Sueur, Cédric1, 2, 3   ; Bousquet, Christophe4, 5  ; Espinosa, Romain6, 7; Deneubourg, Jean-Louis8 
1 Anthropo-Lab, ETHICS EA7446, Lille Catholic University, Lille, France
2 Institut Universitaire de France, Saint-Michel 103, 75005 Paris, France
3 Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France
4 Centre de Recherche en Neurosciences de Lyon, CRNL Inserm U1028, CNRS UMR5292, Université Lyon 1, Lyon, France
5 Laboratoire Cogitamus, https://www.cogitamus.fr/
6 CNRS, CREM – Université Rennes 1, Rennes,France
7 Rennes School of Business, Rennes, France
8 Center for Nonlinear Phenomena and Complex Systems (Cenoli), CP 231, Université Libre de Bruxelles (ULB), Campus Plaine, Boulevard du Triomphe, Building NO, level 5, B-1050, Bruxelles, Belgium

10.24072/pcjournal.31 - Peer Community Journal, Volume 1 (2021), article no. e59.

Get full text PDF Peer reviewed and recommended by PCI

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 criticised 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 individuals (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.

Published online:
DOI: 10.24072/pcjournal.31
Type: Research article
Sueur, Cédric 1, 2, 3; Bousquet, Christophe 4, 5; Espinosa, Romain 6, 7; Deneubourg, Jean-Louis 8

1 Anthropo-Lab, ETHICS EA7446, Lille Catholic University, Lille, France
2 Institut Universitaire de France, Saint-Michel 103, 75005 Paris, France
3 Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France
4 Centre de Recherche en Neurosciences de Lyon, CRNL Inserm U1028, CNRS UMR5292, Université Lyon 1, Lyon, France
5 Laboratoire Cogitamus, https://www.cogitamus.fr/
6 CNRS, CREM – Université Rennes 1, Rennes,France
7 Rennes School of Business, Rennes, France
8 Center for Nonlinear Phenomena and Complex Systems (Cenoli), CP 231, Université Libre de Bruxelles (ULB), Campus Plaine, Boulevard du Triomphe, Building NO, level 5, B-1050, Bruxelles, Belgium
License: CC-BY 4.0
Copyrights: The authors retain unrestricted copyrights and publishing rights 
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Sueur, Cédric; Bousquet, Christophe; Espinosa, Romain; Deneubourg, Jean-Louis. Improving human collective decision-making through animal and artificial intelligence. Peer Community Journal, Volume 1 (2021), article  no. e59. doi : 10.24072/pcjournal.31. https://peercommunityjournal.org/articles/10.24072/pcjournal.31/

Peer reviewed and recommended by PCI : 10.24072/pci.networksci.100002

Conflict of interest of the recommender and peer reviewers:
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.

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