What S in a Name  Experiment on the Aesthetic Judgments of Art Produced by Artificial Intelligence

Israfilzade, Khalil

doi:10.31566/arts.3.011

Cited by 10 publications

(10 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here, we not only wanted to attempt to replicate this finding, but also to determine whether evaluations of different painting types (representational and abstract) differ as a function of whether the purported creator was a human or AI. Research on AI-art perceptions have primarily used abstract paintings as stimuli, which could limit our understanding of the true role of painting type in aesthetic judgements (Israfilzade, 2020;Chiarella, 2022). However, Chamberlain et al (2018) presented varied painting types but found no interaction between painting creator and painting type on general aesthetic value ratings; with our extension of rating criteria, potentially different processes of judgements that may rely both on painting type and creator could be illuminated.…”

Section: Methodsmentioning

confidence: 92%

“…Results of this study indicated that participants tended to prefer the painting that was labeled "human-created" relative to the painting labeled "AI-created." 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 (Israfilzade, 2020;Hong & Curran, 2019;Xu et al, 2020). Additionally, though not an explicit investigation of aesthetic-judgements, per se, one study found that participants were equally likely to consider hypothetical products created by human and AI artists' as "art" (Mikalonytė & Kneer, 2022).…”

Section: Introductionmentioning

confidence: 89%

See 1 more Smart Citation

Humans vs. AI: Whether and why we prefer human-created compared to AI-created artwork

Bellaiche

Shahi²,

Turpin³

et al. 2023

Preprint

View full text Add to dashboard Cite

With the recent proliferation of advanced artificial intelligence (AI) models capable of mimicking human artworks, AI creations might soon replace products of human creativity, although skeptics argue that this outcome is unlikely. One possible reason this may be unlikely is that, independent of the physical properties of art, we place great value on the imbuement of the human experience in art. An interesting question, then, is whether and why people might prefer human- compared to AI-created artworks. To explore these questions, we manipulated the purported creator of pieces of art by randomly assigning a “Human-created” or “AI-created” label to paintings actually created by AI, and then assessed participants’ judgements of the artworks across four rating criteria (Liking, Beauty, Profundity, and Worth). Study 1 found increased positive judgements for human- compared to AI-labeled art across all criteria. Study 2 aimed to replicate and extend Study 1 with additional ratings (Emotion, Story, Meaningful, Effort, and Time to create) intended to elucidate why people more-positively appraise human-labeled artworks. The main findings from Study 1 were replicated, with narrativity (Story) and perceived effort behind artworks (Effort) moderating the label effects (“Human-created” vs. “AI-created”), but only for the sensory-level judgements (Liking, Beauty). Positive personal attitudes towards AI moderated label effects for more-abstract judgements (Profundity, Worth). These studies demonstrate that people tend to be negatively biased against AI-created artworks, which suggests that human engagement in the artistic process contributes positively to our appraisals of art and that, on this basis, AI may not replace human creativity.

show abstract

Section: Methodsmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 89%

Humans vs. AI: Whether and why we prefer human-created compared to AI-created artwork

Bellaiche

Shahi²,

Turpin³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…However, participants (non-experts) in study 1 showed no bias against AI-generated paintings. One explanation was that the label "AI-generated" might make observers feel novel (Israfilzade, 2020). Israfilzade (2020) found that abstract paintings were rated more novel and surprising when artificial intelligence accompanied the title, and no difference was found in terms of complexity, interestingness, and ambiguity arousal of the paintings.…”

Section: Discussionmentioning

confidence: 99%

“…One explanation was that the label "AI-generated" might make observers feel novel (Israfilzade, 2020). Israfilzade (2020) found that abstract paintings were rated more novel and surprising when artificial intelligence accompanied the title, and no difference was found in terms of complexity, interestingness, and ambiguity arousal of the paintings. Moreover, participants in study 1 showed a preference for AI-generated Chinese-style to AI-generated Western-style paintings, in line with the uncertainty-identity hypothesis (Mastandrea et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Who made the paintings: Artists or artificial intelligence? The effects of identity on liking and purchase intention

2022

Front. Psychol.

View full text Add to dashboard Cite

Investigating how people respond to and view AI-created artworks is becoming increasingly crucial as the technology’s current application spreads due to its affordability and accessibility. This study examined how AI art alters people’s evaluation, purchase intention, and collection intention toward Chinese-style and Western-style paintings, and whether art expertise plays a role. Study 1 recruited participants without professional art experience (non-experts) and found that those who made the paintings would not change their liking rating, purchase intention, and collection intention. In addition, they showed ingroup preference, favoring Chinese-style relative to Western-style paintings, in line with previous evidence on cultural preference in empirical aesthetics. Study 2 further investigated the modulation effect of art expertise. Art experts evaluated less favorably (less liking, lower purchase, and collection intentions) AI-generated paintings relative to artist-made paintings, while non-experts showed no preference. There was also an interaction effect between the author and the art expertise and interaction between the painting style and the art expertise. Collectively, the findings in this study showed that who made the art matters for experts and that the painting style affects aesthetic evaluation and ultimate reception of it. These results would also provide implications for AI-art practitioners.

show abstract

“…The emergence of the Internet, the increase of big data, the explosive growth of computer science, and the enormous advancements in robotics and programming have resulted in the development of Artificial Intelligence, which enables it to handle complicated difficulties and tasks. Additionally, this technology appears to generate a variety of various types of content, including dialogues, music, poetry, artwork, film or news scripts, jokes, and creative problem-solving (Israfilzade & Pilelienė, 2018;Akerkar, 2019;Israfilzade, 2020). Latest developments in artificial intelligence have strengthened the effectiveness of powerful tactics such as machine learning and deep neural networks (Wang & Yuan, 2016;Hori et al, 2019;Hussain, Ameri Sianaki & Ababneh, 2019).…”

Section: Introductionmentioning

confidence: 99%

Conversational marketing as a framework for interaction with the customer: Development & validation of the conversational agent's usage scale

Israfilzade

2021

JLECON

Self Cite

View full text Add to dashboard Cite

Conversational agents are becoming an essential part of a growing number of personal and commercial encounters, bringing the issue of Conversational Marketing to a broader audience. A conversational agent is a developing technology that will be used in various fields throughout life, including e-commerce. The common characteristics of any conversational agent in whatever area are their capacity to engage in one-to-one personalised real-time dialogue with a human user and their availability 24 hours a day. Scale items for conversational agent phenomena have not been created scientifically or managerially in a business environment. The primary goal of this study was to develop and validate a new scale for conversational agents that could be used to quantify individual interactions in conversational marketing. As a result, the creation of a new scale for conversational agents with the objective of measuring individual customer interactions in conversational marketing was separated into two phases: Scale Development and Scale Validation. The Conversational Agent Usage Scale was developed and validated as a consequence of pilot studies. Additionally, this article discusses the practical consequences of conversational marketing, which can now be accomplished through the use of the Conversational Agent Usage Scale, which may be used by Customer Service & Support, Marketing, and Sales departments.

show abstract

What S in a Name Experiment on the Aesthetic Judgments of Art Produced by Artificial Intelligence

Cited by 10 publications

References 48 publications

Humans vs. AI: Whether and why we prefer human-created compared to AI-created artwork

Humans vs. AI: Whether and why we prefer human-created compared to AI-created artwork

Who made the paintings: Artists or artificial intelligence? The effects of identity on liking and purchase intention

Conversational marketing as a framework for interaction with the customer: Development & validation of the conversational agent's usage scale

Contact Info

Product

Resources

About