Publikation: Improving human collective decision-making through animal and artificial intelligence
Dateien
Datum
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
Internationale Patentnummer
Link zur Lizenz
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Sammlungen
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Publikationsstatus
Erschienen in
Zusammenfassung
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.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
Schlagwörter
Konferenz
Rezension
Zitieren
ISO 690
SUEUR, Cédric, Christophe BOUSQUET, Romain ESPINOSA, Jean-Louis DENEUBOURG, 2021. Improving human collective decision-making through animal and artificial intelligence. In: Peer Community Journal. Peer Community. 2021, 1, e59. eISSN 2804-3871. Available under: doi: 10.24072/pcjournal.31BibTex
@article{Sueur2021Impro-57034, year={2021}, doi={10.24072/pcjournal.31}, title={Improving human collective decision-making through animal and artificial intelligence}, volume={1}, journal={Peer Community Journal}, author={Sueur, Cédric and Bousquet, Christophe and Espinosa, Romain and Deneubourg, Jean-Louis}, note={Article Number: e59} }
RDF
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/57034"> <dc:rights>terms-of-use</dc:rights> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43"/> <dc:creator>Bousquet, Christophe</dc:creator> <dcterms:abstract xml:lang="eng">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.</dcterms:abstract> <dc:creator>Deneubourg, Jean-Louis</dc:creator> <dc:contributor>Espinosa, Romain</dc:contributor> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/57034/1/Sueur_2-s1re7bh7x2eo1.pdf"/> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-03-29T09:24:45Z</dcterms:available> <dcterms:title>Improving human collective decision-making through animal and artificial intelligence</dcterms:title> <dc:language>eng</dc:language> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-03-29T09:24:45Z</dc:date> <dc:contributor>Deneubourg, Jean-Louis</dc:contributor> <dc:contributor>Bousquet, Christophe</dc:contributor> <dc:contributor>Sueur, Cédric</dc:contributor> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/57034"/> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43"/> <dc:creator>Sueur, Cédric</dc:creator> <foaf:homepage rdf:resource="http://localhost:8080/"/> <dcterms:issued>2021</dcterms:issued> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/57034/1/Sueur_2-s1re7bh7x2eo1.pdf"/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:creator>Espinosa, Romain</dc:creator> </rdf:Description> </rdf:RDF>