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  • 标题:Who Gets Credit for AI-Generated Art?
  • 本地全文:下载
  • 作者:Ziv Epstein ; Sydney Levine ; David G. Rand
  • 期刊名称:iScience
  • 印刷版ISSN:2589-0042
  • 出版年度:2020
  • 卷号:23
  • 期号:9
  • 页码:1-16
  • DOI:10.1016/j.isci.2020.101515
  • 语种:English
  • 出版社:Elsevier
  • 摘要:SummaryThe recent sale of an artificial intelligence (AI)-generated portrait for $432,000 at Christie's art auction has raised questions about how credit and responsibility should be allocated to individuals involved and how the anthropomorphic perception of the AI system contributed to the artwork's success. Here, we identify natural heterogeneity in the extent to which different people perceive AI as anthropomorphic. We find that differences in the perception of AI anthropomorphicity are associated with different allocations of responsibility to the AI system and credit to different stakeholders involved in art production. We then show that perceptions of AI anthropomorphicity can be manipulated by changing the language used to talk about AI—as a tool versus agent—with consequences for artists and AI practitioners. Our findings shed light on what is at stake when we anthropomorphize AI systems and offer an empirical lens to reason about how to allocate credit and responsibility to human stakeholders.Graphical AbstractDisplay OmittedHighlights•There is variation in the extent to which people perceive AI as anthropomorphic•Perception of AI anthropomorphicity is related to allocation of responsibility•Perception of AI anthropomorphicity can be manipulated by changing language•We must be careful with our words when talking about AIComputer Science; Artificial Intelligence; Economics
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