Bias against AI art can enhance perceptions of human creativity

被引:22
作者
Horton, C. Blaine, Jr. [1 ]
White, Michael W. [1 ]
Iyengar, Sheena S. [1 ]
机构
[1] Columbia Business Sch, New York, NY 10027 USA
关键词
ALGORITHMS;
D O I
10.1038/s41598-023-45202-3
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The contemporary art world is conservatively estimated to be a $65 billion USD market that employs millions of human artists, sellers, and collectors globally. Recent attention paid to AI-made art in prestigious galleries, museums, and popular media has provoked debate around how these statistics will change. Unanswered questions fuel growing anxieties. Are AI-made and human-made art evaluated in the same ways? How will growing exposure to AI-made art impact evaluations of human creativity? Our research uses a psychological lens to explore these questions in the realm of visual art. We find that people devalue art labeled as AI-made across a variety of dimensions, even when they report it is indistinguishable from human-made art, and even when they believe it was produced collaboratively with a human. We also find that comparing images labeled as human-made to images labeled as AI-made increases perceptions of human creativity, an effect that can be leveraged to increase the value of human effort. Results are robust across six experiments (N=2965) using a range of human-made and AI-made stimuli and incorporating representative samples of the US population. Finally, we highlight conditions that strengthen effects as well as dimensions where AI-devaluation effects are more pronounced.
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页数:14
相关论文
共 43 条
[1]   AI-powered recommendations: the roles of perceived similarity and psychological distance on persuasion [J].
Ahn, Jungyong ;
Kim, Jungwon ;
Sung, Yongjun .
INTERNATIONAL JOURNAL OF ADVERTISING, 2021, 40 (08) :1366-1384
[2]  
Ballinetti C., 2019, Art Object
[3]  
Barkhorn E., 2010, The Atlantic
[4]  
Baudelaire C., 1955, Mirror Art, P230
[5]  
Ben-Shachar M, 2020, J OPEN SOURCE SOFTW, V5, P2815, DOI [10.21105/joss.02815, 10.21105/joss.02815, DOI 10.21105/JOSS.02815]
[6]  
Burnett T. B., 2023, The Washington Post
[7]   Task-Dependent Algorithm Aversion [J].
Castelo, Noah ;
Bos, Maarten W. ;
Lehmann, Donald R. .
JOURNAL OF MARKETING RESEARCH, 2019, 56 (05) :809-825
[8]   Algorithm Aversion: People Erroneously Avoid Algorithms After Seeing Them Err [J].
Dietvorst, Berkeley J. ;
Simmons, Joseph P. ;
Massey, Cade .
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-GENERAL, 2015, 144 (01) :114-126
[9]  
Edgington K., 2023, Singulart Magazine
[10]  
Elgammal A, 2017, Arxiv, DOI [arXiv:1706.07068, DOI 10.48550/ARXIV.1706.07068]