Artificial intelligence in fine arts: A systematic review of empirical research

Oksanen, Atte; Cvetkovic, Anica; Akin, Nalan; Latikka, Rita; Bergdahl, Jenna; Chen, Yang; Savela, Nina

doi:10.1016/j.chbah.2023.100004

Cited by 15 publications

(8 citation statements)

References 60 publications

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“…At the same time, scientists have begun to examine how image-generating AI is perceived by recipients. Initial research focused on how AI source information alters the aesthetic appreciation of artworks (Di Dio et al, 2023;Messingschlager & Appel, 2023;Oksanen et al, 2023). We connected this relatively young line of research to scientific work on algorithmic bias, which has been a concern for many in the past years (e.g., Angwin et al, 2016;Courtland, 2018).…”

Section: Discussionmentioning

confidence: 99%

“…A match between the technological nature of its creator and supposedly AI-generated content like text or music positively affects responses in studies on generative AI (Hong et al, 2021;Messingschlager & Appel, 2022). In addition, increased moral outrage in case of AI artists might reflect a general aversion against AI generated art (Oksanen et al, 2023;Ragot et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…When it comes to the responses to algorithmic bias in image-generating AI, the perceptions of AI can influence how its pictures are evaluated (Messingschlager & Appel, 2023;Oksanen et al, 2023). Therefore, users' perceptions of the AI as objective could lead to the assumption that its' pictures are unaffected by personal opinions.…”

Section: Study Overview and Predictionsmentioning

confidence: 99%

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Algorithmic Bias in Image-Generating Artificial Intelligence: Prevalence and User Perceptions

Messingschlager,

Appel

2024

Preprint

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Image-generating AI is among the most popular generative AI applications, likely changing the visual mediated environments humans are exposed to on a mass scale. Prior work found that AI can be biased against women and minorities (algorithmic bias), whereas humans attribute rather high objectivity to AI. We focused on image-generating AI, analyzing the extent of algorithmic bias in AI-generated pictures, as well as human responses to bias in image-generating AI. Study 1 showed that AI-generated portraits of people in STEM professions were almost exclusively depicting male, white (and older) individuals. Study 2 (experimental, N = 495) showed that the responses to AI-generated pictures vary, depending on the portrayed group. Participants perceived pictures to be less biased if they were introduced as AI-generated, but only if pictures showed college students (vs. older people). If images showed older people, participants reported higher moral outrage if pictures were supposedly generated by AI (vs. human creators).

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Study Overview and Predictionsmentioning

confidence: 99%

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Algorithmic Bias in Image-Generating Artificial Intelligence: Prevalence and User Perceptions

Messingschlager,

Appel

2024

Preprint

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“…The current development of AI technology is transformative and can be said to be the prominent peak of the Fourth Industrial Revolution [8]. AI is a science and computing technology in the form of an artificial intelligence machine programmed to simulate human intelligence by imitating and practicing human thinking.…”

Section: A Interpretation Of Ai-generated Work In Nft Form As Objects...mentioning

confidence: 99%

“…Regulations regarding trade in digital goods in Indonesia can at least be interpreted in the Government Regulation on Trade via Electronic Systems. In this regulation, the government states that digital goods can be interpreted as any electronic information that produces intangible objects [8] or in the form of converted goods or goods that are in electronic form, such as software, multimedia, and or electronic data [7].…”

Section: B Legal Protection Of Ai Work Traded In the Form Of Nftsmentioning

confidence: 99%

Legal Protection for Copyrighted Works Resulting from Artificial Intelligence which are Traded in the form of Non-Fungible Tokens (NFT)

Arsyad,

Wiwoho

2024

Advances in Social Science, Education and Humanities Research

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This article looks at the protection of works produced by artificial intelligence, interpreted as objects of copyright in Indonesia. This article uses doctrinal research methods. This article answers legal issues regarding trading copyrighted works resulting from Artificial Intelligence in the form of Non-Fungible Tokens. The conceptual approach uses interpretation theory to examine statutory regulations to see the ideal form of recognition of intellectual property rights. The results of this research show that the existence of variations in AI as an object of intellectual property rights and the protection of works produced by AI in the form of Non-Fungible Tokens is protected preventively in the form of a license. Its repression is qualified as an infringement, and trade in works produced by artificial intelligence in Indonesia does not provide certainty because it only regulates in general, not specifically. The research concludes that the Indonesian government needs to review laws related to artificial intelligence and create regulations implementing the trading mechanism for digital copyrighted works in the form of NFTs and resolving disputes.

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The Paradox of Artificial Creativity: Challenges and Opportunities of Generative AI Artistry

Garcia

2024

Creativity Research Journal

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Artificial intelligence in fine arts: A systematic review of empirical research

Cited by 15 publications

References 60 publications

Algorithmic Bias in Image-Generating Artificial Intelligence: Prevalence and User Perceptions

Algorithmic Bias in Image-Generating Artificial Intelligence: Prevalence and User Perceptions

Legal Protection for Copyrighted Works Resulting from Artificial Intelligence which are Traded in the form of Non-Fungible Tokens (NFT)

The Paradox of Artificial Creativity: Challenges and Opportunities of Generative AI Artistry

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