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arXiv:2311.11388cs.CY

Machine Culture

Levin Brinkmann, Fabian Baumann, Jean-François Bonnefon, Maxime Derex, Thomas F. Müller, Anne-Marie Nussberger, Agnieszka Czaplicka, Alberto Acerbi, Thomas L. Griffiths, Joseph Henrich, Joel Z. Leibo, Richard McElreath, Pierre-Yves Oudeyer, Jonathan Stray, Iyad Rahwan

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Abstract

The ability of humans to create and disseminate culture is often credited as the single most important factor of our success as a species. In this Perspective, we explore the notion of machine culture, culture mediated or generated by machines. We argue that intelligent machines simultaneously transform the cultural evolutionary processes of variation, transmission, and selection. Recommender algorithms are altering social learning dynamics. Chatbots are forming a new mode of cultural transmission, serving as cultural models. Furthermore, intelligent machines are evolving as contributors in generating cultural traits--from game strategies and visual art to scientific results. We provide a conceptual framework for studying the present and anticipated future impact of machines on cultural evolution, and present a research agenda for the study of machine culture.

arXiv comments
Journal reference
Nat Hum Behav 7, 1855-1868 (2023)
DOI
doi:10.1038/s41562-023-01742-2
Subjects
cs.CYComputers and Society

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Linked by 1 identifiable commenter in 1 comment across 1 thread, from Apr 2024 to Apr 2024. Found in 1 HN submission from Jan 2024 to Jan 2024. Open submission discussions.

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    • "Decision quality" appears to be average difference in winning probability between player's move versus a move by Alpha Go (Leela Zero). It's on page 16 of: https://doi.org/10.2139/ssrn.3893835 Where it says "Measuring the quality of moves". I found this via citation #31 of…

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