Investigating American and Chinese Subjects' explicit and implicit perceptions of AI-Generated artistic work

Abstract As the prevalence of AI-generated content increases, examining viewers' perceptions of the content is crucial to understanding the human-machine relationship and further facilitating efficient human-machine collaboration. Prior literature has accumulated mixed findings regarding subjects' attitudes toward and perceptions of news and tweets written by natural language generation (NLG) algorithms. To resolve this inconsistency and expand our understanding beyond NLG, this study investigated the explicit and implicit perceptions of AI-generated poetry and painting held by subjects from two societies. An experimental survey was conducted to examine the subjects' explicit and implicit perceptions of AI-generated content in the U.S. and China. As the U.S. and China fiercely compete to lead the development of AI technology, their citizens exhibit divergent attitudes toward AI's performance in artistic work. The U.S. subjects were more critical of the AI- than the human-generated content, both explicitly and implicitly. Although the Chinese subjects were overtly positive about the AI-generated content, they appreciated less this content than the human-authored content. The findings enrich our understanding in the domain of AI generation. Theoretical and practical implications are discussed.

[1]  Glenn R Carroll The organizational construction of authenticity : An examination of contemporary food and dining in the US . Research in Organizat ional Behavior , 2018 .

[2]  Karl F. MacDorman,et al.  Does Japan really have robot mania? Comparing attitudes by implicit and explicit measures , 2008, AI & SOCIETY.

[3]  Patric R. Spence,et al.  Is that a bot running the social media feed? Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twitter , 2014, Comput. Hum. Behav..

[4]  Daniel B. Shank Are computers good or bad for business? How mediated customer-computer interaction alters emotions, impressions, and patronage toward organizations , 2013, Comput. Hum. Behav..

[5]  B. Pelham,et al.  Two Roads to Positive Regard: Implicit and Explicit Self-Evaluation and Culture , 1999 .

[6]  Brian A. Nosek,et al.  A multitrait-multimethod validation of the Implicit Association Test: implicit and explicit attitudes are related but distinct constructs. , 2007, Experimental psychology.

[7]  Brian A. Nosek CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE Implicit–Explicit Relations , 2022 .

[8]  Stuart J. Russell,et al.  Research Priorities for Robust and Beneficial Artificial Intelligence , 2015, AI Mag..

[9]  G. Semin,et al.  Language use in intergroup contexts: the linguistic intergroup bias. , 1989, Journal of personality and social psychology.

[10]  Brian A. Nosek,et al.  Moderators of the relationship between implicit and explicit evaluation. , 2005, Journal of experimental psychology. General.

[11]  A. Maass,et al.  Measuring prejudice: Implicit versus explicit techniques. , 2000 .

[12]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[13]  Andrew Hargadon,et al.  The pleasure principle: immersion, engagement, flow , 2000, HYPERTEXT '00.

[14]  D. Cope Staring Emmy Straight in the Eye—And Doing My Best Not to Flinch , 2004 .

[15]  Clifford Nass,et al.  Computers are social actors , 1994, CHI '94.

[16]  Gianpietro Mazzoleni,et al.  The international encyclopedia of political communication , 2016 .

[17]  Alison A. Plessinger,et al.  Exploring Receivers' Criteria for Perception of Print and Online News , 1999 .

[18]  A. Jacobs,et al.  Immersing in the stillness of an early morning: Testing the mood empathy hypothesis of poetry reception. , 2014 .

[19]  Y. Shoda,et al.  Black and White, or Shades of Gray? Racial Labeling of Barack Obama Predicts Implicit Race Perception , 2010 .

[20]  Alison L. Chasteen,et al.  Private vs Public Expressions of Racial Prejudice , 1996 .

[21]  Taezoon Park,et al.  When stereotypes meet robots: The double-edge sword of robot gender and personality in human-robot interaction , 2014, Comput. Hum. Behav..

[22]  Manfred Tscheligi,et al.  Affect Misattribution Procedure: An implicit technique to measure user experience in HRI , 2012, 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[23]  K. Fiedler,et al.  The cognitive functions of linguistic categories in describing persons: Social cognition and language. , 1988 .

[24]  E. Krahmer,et al.  Journalist versus news consumer : The perceived credibility of machine written news , 2014 .

[25]  Arjen van Dalen,et al.  The algorithms behind the headlines. How machine-written news redefines the core skills of human journalists , 2012 .

[26]  Babak Saleh,et al.  Large-scale Classification of Fine-Art Paintings: Learning The Right Metric on The Right Feature , 2015, ArXiv.

[27]  R. Cialdini,et al.  Social influence: Social norms, conformity and compliance. , 1998 .

[28]  Michael A. Olson,et al.  Implicit Attitude Formation Through Classical Conditioning , 2001, Psychological science.

[29]  S. Sundar,et al.  Multimedia Effects on Processing and Perception of Online News: A Study of Picture, Audio, and Video Downloads , 2000 .

[30]  R. Bornstein,et al.  Perception without Awareness: Cognitive, Clinical and Social Perspectives , 1993 .

[31]  S. Sloman The empirical case for two systems of reasoning. , 1996 .

[32]  Duane T. Wegener,et al.  Matching Versus Mismatching Attitude Functions: Implications for Scrutiny of Persuasive Messages , 1998 .

[33]  Arthur S. Jago,et al.  Algorithms and Authenticity , 2017, Academy of Management Discoveries.

[34]  Robert J. Rydell,et al.  Understanding implicit and explicit attitude change: a systems of reasoning analysis. , 2006, Journal of personality and social psychology.

[35]  M. J. Monteith,et al.  Self-regulation of prejudiced responses: Implications for progress in prejudice-reduction efforts. , 1993 .

[36]  A. Werner Perception Without Awareness: Cognitive, Clinical, and Social Perspectives , 1993 .

[37]  T. Franklin Waddell,et al.  A Robot Wrote This? , 2018 .

[38]  Patrick T. Vargas,et al.  The Linguistic Intergroup Bias As an Implicit Indicator of Prejudice , 1997 .

[39]  L. Rikkers,et al.  The bandwagon effect , 2002, Journal of Gastrointestinal Surgery.

[40]  M. Lombard,et al.  Content Analysis in Mass Communication: Assessment and Reporting of Intercoder Reliability , 2002 .

[41]  Anne Lauscher Life 3.0: being human in the age of artificial intelligence , 2019, Internet Histories.

[42]  Exploring “fabula” and “sjuzhet” in classical Chinese poetry from the perspective of cognitive poetics , 2018, Neohelicon.

[43]  Glenn R. Carroll,et al.  The Organizational Construction of Authenticity: An Examination of Contemporary Food and Dining in the U.S. , 2008 .

[44]  Ben J. A. Kröse,et al.  Assessing Acceptance of Assistive Social Agent Technology by Older Adults: the Almere Model , 2010, Int. J. Soc. Robotics.

[45]  M. Lombard,et al.  Measuring Presence: The Temple Presence Inventory , 2009 .

[46]  S. Sundar The MAIN Model : A Heuristic Approach to Understanding Technology Effects on Credibility , 2007 .

[47]  K. Fiedler,et al.  Language and implicit attributions in the Nuremberg Trials: Analyzing prosecutors' and defense attorneys' closing speeches. , 1996 .

[48]  Diana C. Mutz Impersonal Influence: How Perceptions of Mass Collectives Affect Political Attitudes , 1998 .

[49]  Noam Lemelshtrich Latar The Robot Journalist in the Age of Social Physics: The End of Human Journalism? , 2015 .

[50]  James J. Cummings,et al.  The Use of Media in Media Psychology , 2016 .

[51]  E. Noelle-Neumann The Theory of Public Opinion: The Concept of the Spiral of Silence , 1991 .

[52]  William A. Cunningham,et al.  Implicit Attitude Measures: Consistency, Stability, and Convergent Validity , 2001, Psychological science.

[53]  S. Asch Studies of independence and conformity: I. A minority of one against a unanimous majority. , 1956 .

[54]  M. Banaji,et al.  Implicit social cognition: attitudes, self-esteem, and stereotypes. , 1995, Psychological review.

[55]  Manfred Tscheligi,et al.  Studies in Public Places as a Means to Positively Influence People's Attitude towards Robots , 2012, ICSR.

[56]  S. Jin My avatar behaves well and this feels right: Ideal and ought selves in video gaming , 2011 .

[57]  S. Sherman,et al.  The Explicit and Implicit Perception of In-Group Members Who Use Stereotypes: Blatant Rejection but Subtle Conformity , 2001 .

[58]  Tatsuya Nomura,et al.  The influence of people’s culture and prior experiences with Aibo on their attitude towards robots , 2006, AI & SOCIETY.

[59]  D. Wegner,et al.  Feeling robots and human zombies: Mind perception and the uncanny valley , 2012, Cognition.

[60]  A. Moniz,et al.  Robots Working with Humans or Humans Working with Robots? Searching for Social Dimensions in New Human-Robot Interaction in Industry , 2016 .

[61]  David Caswell,et al.  Automated Journalism 2.0: Event-driven narratives , 2018 .

[62]  Daniel Jurafsky,et al.  A Computational Analysis of Style, Affect, and Imagery in Contemporary Poetry , 2012, CLfL@NAACL-HLT.

[63]  Ass,et al.  Can computers be teammates? , 1996 .

[64]  I. Ajzen The theory of planned behavior , 1991 .

[65]  A. Greenwald,et al.  Measuring individual differences in implicit cognition: the implicit association test. , 1998, Journal of personality and social psychology.

[66]  John Markoff,et al.  Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots , 2015 .

[67]  Xialing Lin,et al.  Evaluations of an artificial intelligence instructor's voice: Social Identity Theory in human-robot interactions , 2019, Comput. Hum. Behav..

[68]  C. McCauley,et al.  Individual differences in sex stereotyping of occupations and personality traits , 1991 .

[69]  Qian Xu,et al.  The bandwagon effect of collaborative filtering technology , 2008, CHI Extended Abstracts.

[70]  A. Graefe,et al.  Readers’ perception of computer-generated news: Credibility, expertise, and readability , 2018 .

[71]  H. Tobi,et al.  Explicit and implicit attitude toward an emerging food technology: The case of cultured meat , 2017, Appetite.