Araştırma Makalesi
BibTex RIS Kaynak Göster

ARTIFICIAL INTELLIGENCE AND COMPARATIVE ANALYSIS OF ART MOVEMENTS: A STUDY ON RENAISSANCE, BAROQUE, IMPRESSIONISM, AND EXPRESSIONISM

Yıl 2025, Sayı: 15- Özel sayı, 613 - 635, 20.10.2025
https://doi.org/10.20488/sanattasarim.1804847

Öz

This study presents a phenomenological analysis of the images produced by Artificial Intelligence
(AI) tools in terms of the characteristics of various art movements such as Renaissance,
Baroque, Impressionism, and Expressionism. The main purpose of the research is to
reveal the extent to which AI images comply with or differ from the characteristics of the
examined art movements—such as line, realism, aesthetics, composition, color, perspective,
abstraction, deformation, anatomy, rhythm, and balance—and to assess whether these
images can be classified as art. In addition, the study includes the analysis of the art movements
within the scope of technology. In the study, the outputs of AI tools in terms of the
given keywords were examined, and visual analysis of the works produced and interviews
with the artists were used as a methodology to determine the extent to which they capture
the essence and characteristics of each art movement. The findings demonstrate how AI
interprets and replicates the stylistic features of various art movements and the degree to
which it can imitate their defining characteristics.

Kaynakça

  • Adeoye-Olatunde, O. A., & Olenik, N. L. (2021). Research and Scholarly Methods: Semi-structured Interviews. JACCP Journal of the American College of Clinical Pharmacy, 4(10), 1358–1367. https://doi.org/10.1002/jac5.1441
  • Aktas, H., & San, B. T. (2019). Landslide Susceptibility Mapping Using an Automatic Sampling Algorithm Based on Two Level Random Sampling. Computers & Geosciences, 133, 104329.
  • Boden, M. A., & Edmonds, E. A. (2009). What Is Generative Art? Digital Creativity, 20(1–2), 21–46. https://doi.org/10.1080/14626260902867915
  • Burgess, R. G. (2002). In The Field: An Introduction to Field Research. Routledge.
  • Cetinic, E., Computing, J. S.-A. T. on M., & 2022, undefined. (2021). Understanding and Creating Art with AI: Review and Outlook. Dl.Acm.OrgE Cetinic, J SheACM Transactions on Multimedia Computing, Communications, and Applications, 2022•dl.Acm.Org. https://dl.acm.org/doi/abs/10.1145/3475799
  • Chaudhry, M. A., & Kazim, E. (2022). Artificial Intelligence in Education (AIEd): A High-level Academic and Industry Note 2021. AI and Ethics, 2(1), 157–165.
  • Cohen, J. E. (2017). Law for the Platform Economy. U.C. Davis Law Review, 51. https://heinonline.org/HOL/Page?handle=hein.journals/davlr51&id=139&div=8&collection=journals
  • Creswell, J. W., Hanson, W. E., Clark Plano, V. L., & Morales, A. (2007). Qualitative Research Designs: Selection and Implementation. The Counseling Psychologist, 35(2), 236–264. https://doi.org/10.1177/0011000006287390
  • Danto, A. C. . (1981). The Transfiguration of the Commonplace : A Philosophy of Art. Harvard University Press. https://books.google.com/books/about/The_Transfiguration_of_the_Commonplace.html?hl=tr&id=LIW60mm5QJkC
  • Dehouche, N., & Dehouche, K. (2023). What’s in a Text-to-image Prompt? The Potential of Stable Diffusion in Visual Arts Education. Heliyon, 9(6).
  • Ebzeeva, Y. N. (2021). QS Subject Focus Summit 2020 on Modern Languages and Linguistics: Languages and migration in a globalized world. Russian Journal of Linguistics, 25(2), 299–316. https://doi.org/10.22363/2687-0088-2021-25-2-299-316
  • Elgammal, A., Liu, B., Kim, D., Elhoseiny, M., & Mazzone, M. (2018). The Shape of Art History in the Eyes of the Machine. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.11894
  • Frechette, J., Bitzas, V., Aubry, M., Kilpatrick, K., & Elanie Lavoie-Tremblay, M. ´. (2020). Capturing Lived Experience: Methodological Considerations for Interpretive Phenomenological Inquiry.
  • International Journal of Qualitative Methods, 19. https://doi.org/10.1177/1609406920907254
  • Groenewald, T. (2004). A Phenomenological Research Design Illustrated. Http://Dx.Doi.Org/10.1177/160940690400300104, 3(1), 42–55. https://doi.org/10.1177/160940690400300104
  • Gross, E. C. (2023). Artificial Intelligence for the Generation of Satirical Articles - An Exploratory Approach. Bulletin of the Transilvania University of Braşov. Series VII: Social Sciences • Law, 231–240. https://doi.org/10.31926/but.ssl.2022.15.64.2.12
  • Groys, Boris. (2016). In the Flow. Verso.
  • Harrison, C., & Wood, P. (2003). Art in Theory, 1900-2000 an Anthology of Changing Ideas. https://philpapers.org/rec/HARAIT-20
  • Honour, H., & Fleming, J. (2005). A World History of Art. https://books.google.com/books?hl=en&lr=&id=qGb4pyoseH4C&oi=fnd&pg=PP14&dq=Honour,+H.,+%26+Fleming,+J.+(2005).+A+World+History+of+Art.+London:+Laurence+King+Publishing.&ots=Uh9j9IoO1O&sig=Z-JjH2W3oHCgWW65tPztnGMDHoo
  • Jill Lloyd. (1991). German Expressionism: Primitivism and Modernity. Cir.Nii.Ac.Jp. https://cir.nii.ac.jp/crid/1130000798116984832
  • John Rewald. (1973). The History of Impressionism. Cir.Nii.Ac.Jp. https://cir.nii.ac.jp/crid/1130000794099485696
  • Karakaya, Ü., & Dayi, H. (2024). The Relationship Between Artifical Intelligence Assisted Image Production And Reality. Akdeniz Sanat, 18(33), 9–31. https://doi.org/10.48069/akdenizsanat.1389695
  • Kleiner, F. S. (2015). Gardner’s Art Through The Ages: A Global History. Cengage Learning.
  • Li, J., & Zhang, B. (2022). The Application of Artificial Intelligence Technology in Art Teaching Taking Architectural Painting as an Example. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/8803957
  • Li, L. (2022). The Impact of Artificial Intelligence Painting on Contemporary Art From Disco Diffusion’s Painting Creation Experiment. International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML).
  • Manovich, Lev. (2002). The Language of New Media. MIT Press.
  • McCormack, J., Gifford, T., & Hutchings, P. (2019). Autonomy, Authenticity, Authorship and Intention in Computer Generated Art. Lecture Notes in Computer Science (Including Subseries Lecture
  • Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11453 LNCS, 35–50. https://doi.org/10.1007/978-3-030-16667-0_3
  • M.Given, L. (2008). The SAGE Encyclopedia of Qualitative Research Methods. The SAGE Encyclopedia of Qualitative Research Methods. https://doi.org/10.4135/9781412963909
  • Muhsen, I. N., Elhassan, T., & Hashmi, S. K. (2018). Artificial intelligence approaches in hematopoietic cell transplantation: A review of the current status and future directions. Turkish Journal of Hematology, 35(3), 152–157. https://doi.org/10.4274/TJH.2018.0123 O’Meara, J., & Murphy, C. (2023). Aberrant AI Creations: Co-creating Surrealist Body Horror Using the DALL-E Mini Text-to-image Generator. Convergence, 29(4), 1070–1096. https://doi.org/10.1177/13548565231185865
  • Rädiker, S., & Kuckartz, U. (2019). Analyse Qualitativer Daten Mit MAXQDA. Analyse Qualitativer Daten Mit MAXQDA. https://doi.org/10.1007/978-3-658-22095-2
  • Raji, I. D., & Buolamwini, J. (2019). Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products. AIES 2019 - Proceedings of the 2019
  • AAAI/ACM Conference on AI, Ethics, and Society, 429–435. https://doi.org/10.1145/3306618.3314244
  • Raveh, A. R., Information, B. T.-, & 2018, undefined. (2018). From homo sapiens to robo sapiens: the evolution of intelligence. Mdpi.ComA Ringel Raveh, B TamirInformation, 2018•mdpi. Com, 10(1). https://doi.org/10.3390/info10010002
  • Salmons, J. (2023). Designing Phenomenological Studies. Sage Research Methods Community.
  • Şen, E. (2021). Dall-e and JL2P on Axis of Data Visualization and Motion A Reviw on. International Journal of Social Sciences, 3(5), 253–280. https://doi.org/10.47994/USBAD.871726
  • Shen, Y., & Yu, F. (2021). The Influence of Artificial Intelligence on Art Design in the Digital Age. Scientific Programming, 2021. https://doi.org/10.1155/2021/4838957
  • Srinivasan, R., arXiv:2102.11957, K. U. preprint, & 2021, undefined. (2021). Quantifying Confounding Bias in Generative Art: A Case Study. Arxiv.OrgR Srinivasan, K UchinoarXiv Preprint ArXiv:2102.11957, 2021•arxiv.Org. https://arxiv.org/abs/2102.11957
  • Tutar, H. (2022). Validity and Reliability in Qualitative Research: A Model Proposal. Anadolu University Journal of Social Science, 22(Special issue 2), 117–140. https://doi.org/10.18037/AUSBD.1227323
  • Wang, L. (2019). The Subjective Value of Artistic Creation in the Age of Artificial Intelligence. 5th International Conference on Arts, Design and Contemporary Education (ICADCE 2019), 60–64.
  • Wolfflin, H. (2009). Principles of Art History. https://www.csus.edu/indiv/o/obriene/art192b/heinrich-wolffin_principles-of-art-history.pdf

YAPAY ZEKA VE SANAT AKIMLARININ KARŞILAŞTIRMALI ANALİZİ: RÖNESANS, BAROK, EMPRESYONİZM VE EKSPRESYONİZM ÜZERİNE BİR ÇALIŞMA

Yıl 2025, Sayı: 15- Özel sayı, 613 - 635, 20.10.2025
https://doi.org/10.20488/sanattasarim.1804847

Öz

Bu çalışma, Yapay Zeka (YZ) araçları tarafından üretilen imgelerin Rönesans, Barok, Ekspresyonizm
ve Empresyonizm gibi çeşitli sanat akımlarının özellikleri açısından fenomenolojik
bir analizini sunmaktadır. Araştırmanın temel amacı, YZ imgelerinin incelenen
sanat akımlarının çizgi, gerçeklik, estetik, kompozisyon, renk, perspektif, soyutlama, deformasyon,
anatomi, ritim ve denge gibi özellikleriyle ne ölçüde örtüştüğünü ya da farklılaştığını
ortaya koymak ve bu imgelerin sanat olarak adlandırılıp adlandırılamayacağını
ortaya koymaktır. Öte yandan çalışma, sanat akımlarının teknoloji kapsamında analizini
de içeriyor. Çalışmada, verilen anahtar kelimeler açısından YZ araçlarının çıktıları incelenmiş
ve üretilen eserlerin görsel analizi ve sanatçılarla yapılan görüşmeler, her bir sanat
akımının özünü ve özelliklerini ne ölçüde yakaladıklarını belirlemek için bir metodoloji
olarak kullanılmıştır. Elde edilen sonuçlar, YZ›nin sanat yaratımında sanat akımlarını nasıl
yorumladığını ve bu akımların karakteristik özelliklerini ne ölçüde taklit edebildiğini
göstermektedir.

Kaynakça

  • Adeoye-Olatunde, O. A., & Olenik, N. L. (2021). Research and Scholarly Methods: Semi-structured Interviews. JACCP Journal of the American College of Clinical Pharmacy, 4(10), 1358–1367. https://doi.org/10.1002/jac5.1441
  • Aktas, H., & San, B. T. (2019). Landslide Susceptibility Mapping Using an Automatic Sampling Algorithm Based on Two Level Random Sampling. Computers & Geosciences, 133, 104329.
  • Boden, M. A., & Edmonds, E. A. (2009). What Is Generative Art? Digital Creativity, 20(1–2), 21–46. https://doi.org/10.1080/14626260902867915
  • Burgess, R. G. (2002). In The Field: An Introduction to Field Research. Routledge.
  • Cetinic, E., Computing, J. S.-A. T. on M., & 2022, undefined. (2021). Understanding and Creating Art with AI: Review and Outlook. Dl.Acm.OrgE Cetinic, J SheACM Transactions on Multimedia Computing, Communications, and Applications, 2022•dl.Acm.Org. https://dl.acm.org/doi/abs/10.1145/3475799
  • Chaudhry, M. A., & Kazim, E. (2022). Artificial Intelligence in Education (AIEd): A High-level Academic and Industry Note 2021. AI and Ethics, 2(1), 157–165.
  • Cohen, J. E. (2017). Law for the Platform Economy. U.C. Davis Law Review, 51. https://heinonline.org/HOL/Page?handle=hein.journals/davlr51&id=139&div=8&collection=journals
  • Creswell, J. W., Hanson, W. E., Clark Plano, V. L., & Morales, A. (2007). Qualitative Research Designs: Selection and Implementation. The Counseling Psychologist, 35(2), 236–264. https://doi.org/10.1177/0011000006287390
  • Danto, A. C. . (1981). The Transfiguration of the Commonplace : A Philosophy of Art. Harvard University Press. https://books.google.com/books/about/The_Transfiguration_of_the_Commonplace.html?hl=tr&id=LIW60mm5QJkC
  • Dehouche, N., & Dehouche, K. (2023). What’s in a Text-to-image Prompt? The Potential of Stable Diffusion in Visual Arts Education. Heliyon, 9(6).
  • Ebzeeva, Y. N. (2021). QS Subject Focus Summit 2020 on Modern Languages and Linguistics: Languages and migration in a globalized world. Russian Journal of Linguistics, 25(2), 299–316. https://doi.org/10.22363/2687-0088-2021-25-2-299-316
  • Elgammal, A., Liu, B., Kim, D., Elhoseiny, M., & Mazzone, M. (2018). The Shape of Art History in the Eyes of the Machine. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.11894
  • Frechette, J., Bitzas, V., Aubry, M., Kilpatrick, K., & Elanie Lavoie-Tremblay, M. ´. (2020). Capturing Lived Experience: Methodological Considerations for Interpretive Phenomenological Inquiry.
  • International Journal of Qualitative Methods, 19. https://doi.org/10.1177/1609406920907254
  • Groenewald, T. (2004). A Phenomenological Research Design Illustrated. Http://Dx.Doi.Org/10.1177/160940690400300104, 3(1), 42–55. https://doi.org/10.1177/160940690400300104
  • Gross, E. C. (2023). Artificial Intelligence for the Generation of Satirical Articles - An Exploratory Approach. Bulletin of the Transilvania University of Braşov. Series VII: Social Sciences • Law, 231–240. https://doi.org/10.31926/but.ssl.2022.15.64.2.12
  • Groys, Boris. (2016). In the Flow. Verso.
  • Harrison, C., & Wood, P. (2003). Art in Theory, 1900-2000 an Anthology of Changing Ideas. https://philpapers.org/rec/HARAIT-20
  • Honour, H., & Fleming, J. (2005). A World History of Art. https://books.google.com/books?hl=en&lr=&id=qGb4pyoseH4C&oi=fnd&pg=PP14&dq=Honour,+H.,+%26+Fleming,+J.+(2005).+A+World+History+of+Art.+London:+Laurence+King+Publishing.&ots=Uh9j9IoO1O&sig=Z-JjH2W3oHCgWW65tPztnGMDHoo
  • Jill Lloyd. (1991). German Expressionism: Primitivism and Modernity. Cir.Nii.Ac.Jp. https://cir.nii.ac.jp/crid/1130000798116984832
  • John Rewald. (1973). The History of Impressionism. Cir.Nii.Ac.Jp. https://cir.nii.ac.jp/crid/1130000794099485696
  • Karakaya, Ü., & Dayi, H. (2024). The Relationship Between Artifical Intelligence Assisted Image Production And Reality. Akdeniz Sanat, 18(33), 9–31. https://doi.org/10.48069/akdenizsanat.1389695
  • Kleiner, F. S. (2015). Gardner’s Art Through The Ages: A Global History. Cengage Learning.
  • Li, J., & Zhang, B. (2022). The Application of Artificial Intelligence Technology in Art Teaching Taking Architectural Painting as an Example. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/8803957
  • Li, L. (2022). The Impact of Artificial Intelligence Painting on Contemporary Art From Disco Diffusion’s Painting Creation Experiment. International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML).
  • Manovich, Lev. (2002). The Language of New Media. MIT Press.
  • McCormack, J., Gifford, T., & Hutchings, P. (2019). Autonomy, Authenticity, Authorship and Intention in Computer Generated Art. Lecture Notes in Computer Science (Including Subseries Lecture
  • Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11453 LNCS, 35–50. https://doi.org/10.1007/978-3-030-16667-0_3
  • M.Given, L. (2008). The SAGE Encyclopedia of Qualitative Research Methods. The SAGE Encyclopedia of Qualitative Research Methods. https://doi.org/10.4135/9781412963909
  • Muhsen, I. N., Elhassan, T., & Hashmi, S. K. (2018). Artificial intelligence approaches in hematopoietic cell transplantation: A review of the current status and future directions. Turkish Journal of Hematology, 35(3), 152–157. https://doi.org/10.4274/TJH.2018.0123 O’Meara, J., & Murphy, C. (2023). Aberrant AI Creations: Co-creating Surrealist Body Horror Using the DALL-E Mini Text-to-image Generator. Convergence, 29(4), 1070–1096. https://doi.org/10.1177/13548565231185865
  • Rädiker, S., & Kuckartz, U. (2019). Analyse Qualitativer Daten Mit MAXQDA. Analyse Qualitativer Daten Mit MAXQDA. https://doi.org/10.1007/978-3-658-22095-2
  • Raji, I. D., & Buolamwini, J. (2019). Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products. AIES 2019 - Proceedings of the 2019
  • AAAI/ACM Conference on AI, Ethics, and Society, 429–435. https://doi.org/10.1145/3306618.3314244
  • Raveh, A. R., Information, B. T.-, & 2018, undefined. (2018). From homo sapiens to robo sapiens: the evolution of intelligence. Mdpi.ComA Ringel Raveh, B TamirInformation, 2018•mdpi. Com, 10(1). https://doi.org/10.3390/info10010002
  • Salmons, J. (2023). Designing Phenomenological Studies. Sage Research Methods Community.
  • Şen, E. (2021). Dall-e and JL2P on Axis of Data Visualization and Motion A Reviw on. International Journal of Social Sciences, 3(5), 253–280. https://doi.org/10.47994/USBAD.871726
  • Shen, Y., & Yu, F. (2021). The Influence of Artificial Intelligence on Art Design in the Digital Age. Scientific Programming, 2021. https://doi.org/10.1155/2021/4838957
  • Srinivasan, R., arXiv:2102.11957, K. U. preprint, & 2021, undefined. (2021). Quantifying Confounding Bias in Generative Art: A Case Study. Arxiv.OrgR Srinivasan, K UchinoarXiv Preprint ArXiv:2102.11957, 2021•arxiv.Org. https://arxiv.org/abs/2102.11957
  • Tutar, H. (2022). Validity and Reliability in Qualitative Research: A Model Proposal. Anadolu University Journal of Social Science, 22(Special issue 2), 117–140. https://doi.org/10.18037/AUSBD.1227323
  • Wang, L. (2019). The Subjective Value of Artistic Creation in the Age of Artificial Intelligence. 5th International Conference on Arts, Design and Contemporary Education (ICADCE 2019), 60–64.
  • Wolfflin, H. (2009). Principles of Art History. https://www.csus.edu/indiv/o/obriene/art192b/heinrich-wolffin_principles-of-art-history.pdf
Toplam 41 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Resim
Bölüm Makaleler
Yazarlar

Umut Kayapınar 0000-0003-2146-6769

Yayımlanma Tarihi 20 Ekim 2025
Gönderilme Tarihi 12 Mart 2025
Kabul Tarihi 30 Haziran 2025
Yayımlandığı Sayı Yıl 2025 Sayı: 15- Özel sayı

Kaynak Göster

APA Kayapınar, U. (2025). ARTIFICIAL INTELLIGENCE AND COMPARATIVE ANALYSIS OF ART MOVEMENTS: A STUDY ON RENAISSANCE, BAROQUE, IMPRESSIONISM, AND EXPRESSIONISM. Sanat ve Tasarım Dergisi(15- Özel sayı), 613-635. https://doi.org/10.20488/sanattasarim.1804847