Academic Journal
Generative Models for the Psychology of Art and Aesthetics.
| Τίτλος: | Generative Models for the Psychology of Art and Aesthetics. |
|---|---|
| Συγγραφείς: | Hertzmann, Aaron |
| Πηγή: | Empirical Studies of the Arts; Jan2025, Vol. 43 Issue 1, p23-43, 21p |
| Θεματικοί όροι: | Generative artificial intelligence, Psychology of art, Artistic creation, Aesthetics of art, Computer graphics |
| Περίληψη: | This paper describes how computational generative models can describe aspects of the artistic process, and how these generative models can provide tools for formulating and testing psychological theories of art. The term "generative models" here refers to algorithms that can generate artistic imagery, video, text, or other artistic media, including techniques developed in both computer graphics and AI research. Generative models can both describe artistic processes and offer useful experimental tools. This paper first outlines different ways to understand the types of research in generative models. It then surveys several recent examples of using generative models to develop theories and to perform experiments. The paper then discusses misleading uses of the concept of "AI-generated art" in psychological studies, and the need for study of our relationship with new artistic technologies. Finally, the paper offers a few remarks on pursuing interdisciplinary research across psychology and computer graphics. [ABSTRACT FROM AUTHOR] |
| Copyright of Empirical Studies of the Arts is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Generative Models for the Psychology of Art and Aesthetics. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hertzmann%2C+Aaron%22">Hertzmann, Aaron</searchLink> – Name: TitleSource Label: Source Group: Src Data: Empirical Studies of the Arts; Jan2025, Vol. 43 Issue 1, p23-43, 21p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Psychology+of+art%22">Psychology of art</searchLink><br /><searchLink fieldCode="DE" term="%22Artistic+creation%22">Artistic creation</searchLink><br /><searchLink fieldCode="DE" term="%22Aesthetics+of+art%22">Aesthetics of art</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+graphics%22">Computer graphics</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper describes how computational generative models can describe aspects of the artistic process, and how these generative models can provide tools for formulating and testing psychological theories of art. The term "generative models" here refers to algorithms that can generate artistic imagery, video, text, or other artistic media, including techniques developed in both computer graphics and AI research. Generative models can both describe artistic processes and offer useful experimental tools. This paper first outlines different ways to understand the types of research in generative models. It then surveys several recent examples of using generative models to develop theories and to perform experiments. The paper then discusses misleading uses of the concept of "AI-generated art" in psychological studies, and the need for study of our relationship with new artistic technologies. Finally, the paper offers a few remarks on pursuing interdisciplinary research across psychology and computer graphics. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Empirical Studies of the Arts is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edb&AN=180922073 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1177/02762374241288696 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 23 Subjects: – SubjectFull: Generative artificial intelligence Type: general – SubjectFull: Psychology of art Type: general – SubjectFull: Artistic creation Type: general – SubjectFull: Aesthetics of art Type: general – SubjectFull: Computer graphics Type: general Titles: – TitleFull: Generative Models for the Psychology of Art and Aesthetics. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hertzmann, Aaron IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 02762374 Numbering: – Type: volume Value: 43 – Type: issue Value: 1 Titles: – TitleFull: Empirical Studies of the Arts Type: main |
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