动物的文化传播
计算机科学
变化(天文学)
透视图(图形)
选择(遗传算法)
传播
人工智能
推荐系统
认知科学
机器学习
数据科学
社会学
心理学
生物
电信
遗传学
物理
天体物理学
作者
Levin Brinkmann,Fabian Baumann,Jean‐François Bonnefon,Maxime Derex,Thomas 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
标识
DOI:10.1038/s41562-023-01742-2
摘要
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. Artificial intelligence tools and systems are increasingly influencing human culture. Brinkmann et al. argue that these 'intelligent machines' are transforming the fundamental processes of cultural evolution: variation, transmission and selection.
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