A new sociology of humans and machines.
Journal
Nature human behaviour
ISSN: 2397-3374
Titre abrégé: Nat Hum Behav
Pays: England
ID NLM: 101697750
Informations de publication
Date de publication:
Oct 2024
Oct 2024
Historique:
received:
13
02
2024
accepted:
03
09
2024
medline:
23
10
2024
pubmed:
23
10
2024
entrez:
22
10
2024
Statut:
ppublish
Résumé
From fake social media accounts and generative artificial intelligence chatbots to trading algorithms and self-driving vehicles, robots, bots and algorithms are proliferating and permeating our communication channels, social interactions, economic transactions and transportation arteries. Networks of multiple interdependent and interacting humans and intelligent machines constitute complex social systems for which the collective outcomes cannot be deduced from either human or machine behaviour alone. Under this paradigm, we review recent research and identify general dynamics and patterns in situations of competition, coordination, cooperation, contagion and collective decision-making, with context-rich examples from high-frequency trading markets, a social media platform, an open collaboration community and a discussion forum. To ensure more robust and resilient human-machine communities, we require a new sociology of humans and machines. Researchers should study these communities using complex system methods; engineers should explicitly design artificial intelligence for human-machine and machine-machine interactions; and regulators should govern the ecological diversity and social co-development of humans and machines.
Identifiants
pubmed: 39438685
doi: 10.1038/s41562-024-02001-8
pii: 10.1038/s41562-024-02001-8
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
1864-1876Subventions
Organisme : Irish Research Council (An Chomhairle um Thaighde in Éirinn)
ID : IRCLA/2022/3217
Informations de copyright
© 2024. Springer Nature Limited.
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