Humans versus AI: whether and why we prefer human-created compared to AI-created artwork

“Linear mixed-effects models using maximum likelihood estimation were estimated in R (version 4.2.0; R Core Team, 2022) using the {lme4} package (version 1.1.33; Bates et al., 2015).”

“…cascade of evaluations, implicating more-complex and elaborative processes in judgements of art that seek to understand meaning and communication through the piece (Berlyne, 1960, 1971; Chatterjee & Vartanian, 2016; Cupchik & Berlyn, 1979; Graf & Landwehr, 2015; Leder et al., 2004; Silvia, 2005).”

“Though contention ensues over whether artificial programs are capable of producing “creative” products (in line with the computer science principle known as the Lovelace Objection; Natale & Henrickson, 2022), it is nonetheless critical to understand how audiences perceive such art given that contemporary psychological…”

“…e.g., Margulis et al., 2019; McAuley et al., 2021), the act of deriving meaning from artwork that is often posited in models of aesthetics (e.g., Leder et al., 2004; Pelowski et al., 2017), and that effort and time involved in creation of a product is often a heuristic for quality (Kruger…”

“…the extant literature on the role of labels in subjective evaluations—both in aesthetics and other domains of preferences (e.g., Kirk et al., 2009; McClure et al., 2004; Newman & Bloom, 2012; Plassmann et al., 2008; Turpin et al., 2019)—our findings demonstrate that labels significantly…”

“…in subjective evaluations—both in aesthetics and other domains of preferences (e.g., Kirk et al., 2009; McClure et al., 2004; Newman & Bloom, 2012; Plassmann et al., 2008; Turpin et al., 2019)—our findings demonstrate that labels significantly influence people’s judgements of visual artworks.”

“Before rating the images, participants were asked to complete the 7-item cognitive reflection test (CRT; Frederick, 2005; Toplak et al., 2014).”

“Participants also completed the General Attitudes toward Artificial Intelligence Scale (GAAIS) to assess positive and negative sentiments of AI in general (Schepman & Rodway, 2020).”

“Past work with the CRT has found negative relationships between CRT scores and perceived profundity of randomly generated statements (Pennycook et al., 2015), implying a relationship between cognitive reflection traits and subjective judgements of profundity that could extend to aesthetics.”

“The 20-item GAAIS has been fully validated and found to report a consistent positive subscale (⍺ = 0.88) and negative subscale (⍺ = 0.82), with strong convergent validity with other AI-related measures (Schepman & Rodway, 2022).”

“Other personality traits explored in aesthetics and creativity research include empathy and embodied cognitions (Freedberg & Gallese, 2007; Rusu, 2017), and beliefs of creative mindsets (Hass et al., 2016; Karwowski, 2014).”

“…that can produce, as purely physical stimuli, high-quality artworks that are indiscernible from human-created artworks (Gangadharbatla, 2022; Johnson, 1997; Mazzone & Elgammal, 2019), the Computer Age in which we live has afforded considerable experimental control over these two conceptions of art.”

“…et al., 2019; McAuley et al., 2021), the act of deriving meaning from artwork that is often posited in models of aesthetics (e.g., Leder et al., 2004; Pelowski et al., 2017), and that effort and time involved in creation of a product is often a heuristic for quality (Kruger et al., 2004).”

“(2004), people use effort as a metric to inform their judgements of the quality of a product (e.g., poems, paintings, suits of armor; Kruger et al., 2004).”

“In fact, several recent studies have reported similar anti-AI findings in music (Shank et al., 2022), creative writing (Raj et al., 2023), dance (Darda & Cross, 2023), poetry (Köbis & Mossink, 2020), and non-art texts (Darda et al., 2023).”

“In line with the extant literature on the role of labels in subjective evaluations—both in aesthetics and other domains of preferences (e.g., Kirk et al., 2009; McClure et al., 2004; Newman & Bloom, 2012; Plassmann et al., 2008; Turpin et al., 2019)—our findings demonstrate that labels…”

“…can also assess Consciousness, Extraversion, Agreeableness, and Neuroticism, we chose to implement only the Openness subset given its previous specific involvement in aesthetic encounters (Kaufman, 2013; McCrae, 2007; McCrae & Greenberg, 2014; Silvia et al., 2015), and to reduce study length.”

“These latter criteria require higher cognitive elaboration to determine communicative properties of art, as discussed in Graf and Landwehr (2015) and Sherman and Morrissey (2017).”

“…for marketing and product branding, as it is reminiscent of the mass production advertising practices in the early twentieth century where consumers were overall hesitant to purchase goods from multinational conglomerates until narratives were paired with the product (Freeman, 2014; Pulizzi, 2012).”

“…can also assess Consciousness, Extraversion, Agreeableness, and Neuroticism, we chose to implement only the Openness subset given its previous specific involvement in aesthetic encounters (Kaufman, 2013; McCrae, 2007; McCrae & Greenberg, 2014; Silvia et al., 2015), and to reduce study length.”

“…can also assess Consciousness, Extraversion, Agreeableness, and Neuroticism, we chose to implement only the Openness subset given its previous specific involvement in aesthetic encounters (Kaufman, 2013; McCrae, 2007; McCrae & Greenberg, 2014; Silvia et al., 2015), and to reduce study length.”

“Third, given that aesthetic appraisals are personal and subjective (Chatterjee, 2014; Roseman & Evdokas, 2004), also imperative in their investigation is consideration of individual differences that might reliably predict these judgements.”

“Other emerging models have since provided more nuance to Berlyne’s traditional behaviorist approach (see Berlyne, 1975; Silvia, 2005), including more cognitive principles, and an increased understanding of the processes people utilize to engage with art.”

“…to empathize with other agents, including AI, perhaps explaining AI-art judgements), openness to experience (given its role in aesthetic encounters; Kaufman, 2013; McCrae, 2007; McCrae & Greenberg, 2014; Silvia et al., 2015), personal attitudes toward AI (which we hypothesized could predict…”

“, those that were false in cases wherein the labels indicated that the artworks were created by a human), although we can nevertheless minimize these concerns (at least to some extent) by considering the past literature showing participants’ inability to discriminate between AI- and human-created paintings (Chamberlai…”

“Critically, however, other studies have yielded results that are at odds with those from the aforementioned studies, finding little-to-no differences in evaluations of human- and AI-created artworks (Hong & Curran, 2019; Israfilzade, 2020; Xu et al., 2020).”

“In addition, openness has been shown to influence judgements of art depending on painting type, such that people who are more open to experience tend to have an increased appreciation for abstract art compared to less-open participants (Feist & Brady, 2004).”

“…nevertheless emerged across peoples’ aesthetic judgements of such artworks (e.g., blue is the most preferred color, whereas yellow is most disliked [Bornstein, 1975; Komar & Melamid, 1999; Palmer et al., 2013]; and representational art is enjoyed over abstract art [Heinrichs & Cupchik, 1985;…”

“In other words, people consider non-sensory aspects of art, like context and background, in their judgements and evaluations of art (Blank et al., 1984; Chatterjee & Vartanian, 2016; Winner, 1982).”

“…considers creativity to be not an absolute construct, but a consequence of changing interactions between subjective criteria and socio-cultural factors like technology (i.e., “in the eye of the beholder”; Amabile, 1982; Cseh & Jeffries, 2019; Hennessey et al., 2011; Kaufman & Sternberg, 2010).”

“It can encapsulate and communicate our emotions, be used to express our individualistic and communal experiences, and serve as a social commentary on these experiences, all of which are elements that are commonly thought to be human-specific (Chatterjee, 2014).”

“Other personality traits explored in aesthetics and creativity research include empathy and embodied cognitions (Freedberg & Gallese, 2007; Rusu, 2017), and beliefs of creative mindsets (Hass et al., 2016; Karwowski, 2014).”

“Art created by AI has been met with both success and controversy (see Chatterjee, 2022); and, very recently, these creative products have permeated into mainstream culture like museums and artistic industries (Diaz, 2022; Kaleagasi, 2017; Kinsella, 2018; Zulić, 2019).”

“…across peoples’ aesthetic judgements of such artworks (e.g., blue is the most preferred color, whereas yellow is most disliked [Bornstein, 1975; Komar & Melamid, 1999; Palmer et al., 2013]; and representational art is enjoyed over abstract art [Heinrichs & Cupchik, 1985; Kettlewell et al.,…”

“, those that were false in cases wherein the labels indicated that the artworks were created by a human), although we can nevertheless minimize these concerns (at least to some extent) by considering the past literature showing participants’ inability to discriminate between AI- and human-created paintings (Chamberlai…”

“Similar findings emerged in a more-recent study in which participants were shown, and asked to provide judgements of, two abstract paintings (Chiarella et al., 2022).”

“This is supported, in part, by the growing discussion of art not only as a bottom-up appraisal of only visual features that induces liking or judgements of beauty, but a device for communication and socio-epistemic value (see Sherman & Morrissey, 2017).”

“Such work (e.g., Margulis et al., 2019; McAuley et al., 2021) finds interesting cross-cultural differences, implicating the role of media in our consumption of art and underlying associations (see Wu et al., 2020 for a cross-cultural study that finds higher appreciation for AI products of art…”

“…whether artificial programs are capable of producing “creative” products (in line with the computer science principle known as the Lovelace Objection; Natale & Henrickson, 2022), it is nonetheless critical to understand how audiences perceive such art given that contemporary psychological…”

“In fact, several recent studies have reported similar anti-AI findings in music (Shank et al., 2022), creative writing (Raj et al., 2023), dance (Darda & Cross, 2023), poetry (Köbis & Mossink, 2020), and non-art texts (Darda et al., 2023).”

“…(e.g., blue is the most preferred color, whereas yellow is most disliked [Bornstein, 1975; Komar & Melamid, 1999; Palmer et al., 2013]; and representational art is enjoyed over abstract art [Heinrichs & Cupchik, 1985; Kettlewell et al., 1990; Knapp & Wulff, 1963; Mastandrea et al., 2011, 2021]).”

“Art created by AI has been met with both success and controversy (see Chatterjee, 2022); and, very recently, these creative products have permeated into mainstream culture like museums and artistic industries (Diaz, 2022; Kaleagasi, 2017; Kinsella, 2018; Zulić, 2019).”

“In other words, people consider non-sensory aspects of art, like context and background, in their judgements and evaluations of art (Blank et al., 1984; Chatterjee & Vartanian, 2016; Winner, 1982).”

“In fact, several recent studies have reported similar anti-AI findings in music (Shank et al., 2022), creative writing (Raj et al., 2023), dance (Darda & Cross, 2023), poetry (Köbis & Mossink, 2020), and non-art texts (Darda et al., 2023).”

“Other emerging models have since provided more nuance to Berlyne’s traditional behaviorist approach (see Berlyne, 1975; Silvia, 2005), including more cognitive principles, and an increased understanding of the processes people utilize to engage with art.”

“…(e.g., blue is the most preferred color, whereas yellow is most disliked [Bornstein, 1975; Komar & Melamid, 1999; Palmer et al., 2013]; and representational art is enjoyed over abstract art [Heinrichs & Cupchik, 1985; Kettlewell et al., 1990; Knapp & Wulff, 1963; Mastandrea et al., 2011, 2021]).”

“In fact, several recent studies have reported similar anti-AI findings in music (Shank et al., 2022), creative writing (Raj et al., 2023), dance (Darda & Cross, 2023), poetry (Köbis & Mossink, 2020), and non-art texts (Darda et al., 2023).”

“…(e.g., blue is the most preferred color, whereas yellow is most disliked [Bornstein, 1975; Komar & Melamid, 1999; Palmer et al., 2013]; and representational art is enjoyed over abstract art [Heinrichs & Cupchik, 1985; Kettlewell et al., 1990; Knapp & Wulff, 1963; Mastandrea et al., 2011, 2021]).”

“Such work (e.g., Margulis et al., 2019; McAuley et al., 2021) finds interesting cross-cultural differences, implicating the role of media in our consumption of art and underlying associations (see Wu et al., 2020 for a cross-cultural study that finds higher appreciation for AI products of art…”

“, 2023), dance (Darda & Cross, 2023), poetry (Köbis & Mossink, 2020), and non-art texts (Darda et al., 2023).”

“…(e.g., blue is the most preferred color, whereas yellow is most disliked [Bornstein, 1975; Komar & Melamid, 1999; Palmer et al., 2013]; and representational art is enjoyed over abstract art [Heinrichs & Cupchik, 1985; Kettlewell et al., 1990; Knapp & Wulff, 1963; Mastandrea et al., 2011, 2021]).”

“Critically, however, other studies have yielded results that are at odds with those from the aforementioned studies, finding little-to-no differences in evaluations of human- and AI-created artworks (Hong & Curran, 2019; Israfilzade, 2020; Xu et al., 2020).”

“…(e.g., blue is the most preferred color, whereas yellow is most disliked [Bornstein, 1975; Komar & Melamid, 1999; Palmer et al., 2013]; and representational art is enjoyed over abstract art [Heinrichs & Cupchik, 1985; Kettlewell et al., 1990; Knapp & Wulff, 1963; Mastandrea et al., 2011, 2021]).”

“Other personality traits explored in aesthetics and creativity research include empathy and embodied cognitions (Freedberg & Gallese, 2007; Rusu, 2017), and beliefs of creative mindsets (Hass et al., 2016; Karwowski, 2014).”

“Research on AI-art perceptions has primarily used abstract paintings as stimuli, which could limit our understanding of the true role of painting type in aesthetic judgements (Chiarella et al., 2022; Israfilzade, 2020).”

“However, for experts to have a harsher anti-AI bias than non-experts also goes against claims that “novices are… more non-aesthetically biased in their aesthetic judgments compared with experts,” which suggests that experts are more resistant to label effects (Lundy & Smith, 2017, p. 140).”

“Specifically, Mockros (1993) reported that general aesthetic judgements were rated higher by novice professional adults than novice undergraduates.”

“Various studies have examined the differences in perception and valuation between human-created and AI-generated artwork (Bellaiche et al., 2023; Chiarella et al., 2022).”

“…by AI than when told the poem is written by a human poet (two-sided Welch’s t (4571.552) = –17.398, p 0.0001, p Bonf 0.0001, Mean difference = –0.814, Cohen’s d = -0.508, 99.5% CI –0.945 to –0.683), confirming earlier findings that participants are biased against AI authorship 2,7,15 .”