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Gerçekötesi Dönemde Yapay Zekanın Fotoğraf ve Resim Sanatlarına Etkisi ve Yaratıcılık ile Sahiplik Sorunları

Year 2021, Volume: 7 Issue: 2, 243 - 270, 30.12.2021
https://doi.org/10.46641/medeniyetsanat.994950

Abstract

Sanatta, özellikle görsel sanatlarda insanlar, görüntülerin özü ve tasarımı arasındaki çok yönlü etkileşimi birleştirerek ayırt edici deneyimler yaratma becerilerini mükemmelleştirmiştir. Bu sürecin doğuştan gelen mekanizmaları henüz bilinmemektedir ve benzer yeteneklere sahip yapay bir sistem de mevcut değildir. Bununla birlikte, sanatta yapay zekanın ortaya çıkışı ve artan yaygınlığı, sanatsal yaratıcılık ve sanat eserlerinin yazarlığı gibi temel sabitler gibi görünen şeyleri büyük ölçüde değiştirmeye başlamıştır. Gerçekler, birbiriyle rekabet halindeki versiyonlarda kurguya dönüştükçe, bu fenomen gerçekötesi çağda daha da yaygın hale gelmektedir. Sanat her zaman gerçeklerin peşinde olmasa da üretken çekişmeli ağlar tarafından desteklenen yapay zekâ, sanat kavramını çok daha geniş bir bağlama yerleştirmektedir. Böyle bir bağlamda, gerçekötesi dönemde yapay zekanın fotoğraf ve resim sanatlarına etkisini ve yaratıcılık ile sahiplik sorunlarını tartışmayı amaçlayan ve literatür taramasına dayanan bu betimsel-nitel çalışma, önce üretken çekişmeli ağlar kavramını açıklamakta ve daha sonra fotoğraf ve resimdeki kullanımlarından oluşan bir örneklemi somut örneklerle incelemektedir. Daha sonra, çalışma, üretken çekişmeli ağlar tarafından yönlendirilen yapay zekanın sanat piyasası üzerindeki etkilerini tartışmakta ve bu etkilerden dolayı yaratıcılık kavramını ve sahiplik konusunu sanat eserleri bağlamında analiz etmektedir. Son olarak gerçekötesi kavramı açıklanmakta ve gerçekötesi çerçevede yapay zekanın ortaya çıkışının sanat için gelecekteki yansımaları sorgulanmaktadır. Sonuçlar sanatın ifade ve kanıtlama işlevleri arasındaki çizgilerin bulanıklaşmaya başladığını, aynı zamanda kurgu ve gerçeklik arasındaki sınırın da giderek daha da belirsizleştiğini göstermektedir. Üretken çekişmeli ağlar tarafından desteklenen yapay zekâ, yeni bir ortam veya teknoloji ortaya çıktığında ve giderek daha fazla insan tarafından çeşitli hızlarda ve oranlarda benimsendiğinde olduğu gibi, sanatsal çabalardaki gerçeğin anlamını yeniden bağlamsallaştırmaktadır.

References

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  • Alemoru, K. (2019, March 7). AI artwork flops at auction, robot apocalypse not here yet. Dazed Digital. https://www.dazeddigital.com/art-photography/article/43628/1/klingemannai-ai-auction-first-european-piece-disappointment
  • Antipov, G., Baccouche, M., Dugelay, J.L. (2017, September 17-20). Face aging with conditional generative adversarial networks. [Paper presentation] Proceedings of IEEE International Conference on Image Processing (ICIP), pp. 2089 – 2093. Beijing, China. https://doi.org/10.1109/ICIP.2017.8296650
  • Arendt, H. (1972). Crises of the Republic: Lying in Politics, Civil Disobedience on Violence, Thoughts on Politics, and Revolution. Harcourt Brace Jovanovich.
  • Baudrillard, J. (2020). Simülakrlar ve Simülasyon (trans. Oğuz Adanır). Doğu Batı Yayınları.
  • Benjamin, W. (1969). The Work of Art in the Age of Mechanical Reproduction. In H. Arendt (ed.), Illuminations (pp. 217-251). Schocken Books.
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  • Dangerfield, K. (2020, December 24). Queen Elizabeth’s deepfake Christmas message a ‘stark warning’. Global News. https://globalnews.ca/news/7540882/queen-elizabeth-deepfake-christmas-message/
  • De Mántaras, R. L. (2017). Artificial Intelligence and the Arts: Toward Computational Creativity. In F. Gonzales (ed.), The Next Step-Exponential Life (pp. 100-124). BBVA & The Open Mind.
  • Elgammal, A. (2018, October 29). What the Art World Is Failing to Grasp about Christie’s AI Portrait Coup. Artsy. https://www.artsy.net/article/artsy-editorial-art-failing-grasp-christies-ai-portrait-coup
  • Elgammal, A., Liu, B., Elhoseiny, M., Mazzone, M. (2017, June 20-22). CAN: Creative Adversarial Networks, Generating "Art" by Learning About Styles and Deviating from Style Norms. [Paper presentation]. Proceedings of 8th International Conference on Computational Creativity (ICCC), pp. 96-103. Atlanta, GA, USA. https://computationalcreativity.net/iccc2017/ICCC_17_accepted_submissions/ICCC-17_paper_47.pdf
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  • Heit, H. (2018). “there are no facts”: Nietzsche as Predecessor of Post-Truth?, Studia Philosophica Estonica, 11(1), 44-63. http://dx.doi.org/10.12697/spe.2018.11.1.03
  • Itzkoff, D. (2016, December 27). How ‘Rogue One’ Brought Back Familiar Faces. The New York Times. https://www.nytimes.com/2016/12/27/movies/how-rogue-one-brought-back-grand-moff-tarkin.html
  • Jin, Y., Zhang, J., Li, M., Tian, Y., Zhu, H., Fang, Z. (2017, August 11-13). Towards the Automatic Anime Characters Creation with Generative Adversarial Networks. [Paper presentation]. Comiket 92, pp. 1-16. Tokyo, Japan. https://arxiv.org/pdf/1708.05509.pdf
  • Kinariwala, T. (2019, December 16). Generating Art From Neural Networks. Worldquant. https://www.weareworldquant.com/en/thought-leadership/generating-art-from-neural-networks/
  • Kreitner, R. (2016, November 30). Post-Truth and Its Consequences: What a 25-Year-Old Essay Tells Us About the Current Moment. The Nation. https://www.thenation.com/article/archive/post-truth-and-its-consequences-what-a-25-year-old-essay-tells-us-about-the-current-moment/
  • Kwok, A. O. J., Koh, S. G. M. (2020). Deepfake: a social construction of technology perspective. Current Issues in Tourism, 1-5. https://doi.org/10.1080/13683500.2020.1738357
  • Ledig, C., Theis, L., Huszar, F., Caballero, J., Cunningham, A., Acosta, A., Aitken, A., Tejani A., Totz, J., Wang, Z., Shi, W. (2017, July 21-26). Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. [Paper presentation]. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 105 – 114. Honolulu, HI, USA. https://doi.org/10.1109/CVPR.2017.19
  • Lee, D. (2019, May 19). Deepfake Salvador Dalí takes selfies with museum visitors. The Verge. https://www.theverge.com/2019/5/10/18540953/salvador-dali-lives-deepfake-museum
  • Lyons, K. (2020, January 20). FTC says the tech behind audio deepfakes is getting better. The Verge. https://www.theverge.com/2020/1/29/21080553/ftc-deepfakes-audio-cloning-joe-rogan-phone-scams
  • Lyotard, J. F. (2013). Postmodern Durum (trans. Ahmet Çiğdem). Bilgesu Yayınları.
  • McIntyre, L. C. (2018). Post-truth. MIT Press.
  • Morris, I. (2018, February 5). Revenge 'Porn' Gets Even More Horrifying With Deepfakes. Forbes. https://www.forbes.com/sites/ianmorris/2018/02/05/fakeapp-allows-anyone-to-make-deepfake-porn-of-anyone/?sh=d4dd09c391c9
  • Naumann, F. M. (2012). The Recurrent, Haunting Ghost: Essays on the Art, Life and Legacy of Marcel Duchamp. Readymade Press.
  • Nicholson, C. (2020). A Beginner's Guide to Generative Adversarial Networks (GANs). Pathmind. https://wiki.pathmind.com/generative-adversarial-network-gan
  • O’Neil, L. (2019, June 12). Doctored video of sinister Mark Zuckerberg puts Facebook to the test. The Guardian. https://www.theguardian.com/technology/2019/jun/11/deepfake-zuckerberg-instagram-facebook
  • Oxford Languages. (2016). Word of the Year 2016. https://languages.oup.com/word-of-the-year/2016/
  • Oxford Learner’s Dictionaries. (2021). Post-truth. In Oxford Learner’s Dictionaries.com dictionary. https://www.oxfordlearnersdictionaries.com/definition/english/post-truth?q=post-truth
  • Paris, B., Donovan, J. (2019). Deepfakes and Cheap Fakes: The Manipulation of Audio and Visual Evidence. Data & Society. https://datasociety.net/wp-content/uploads/2019/09/DS_Deepfakes_Cheap_FakesFinal-1-1.pdf
  • Parkin, S. (2019, June 22). ‘Politicians fear this like fire’. The Guardian. https://www.theguardian.com/technology/ng-interactive/2019/jun/22/the-rise-of-the-deepfake-and-the-threat-to-democracy
  • Perarnau, G., Van de Weijer, J., Raducanu, B., Álvarez, J. M. (2016, December 5-10). Invertible Conditional GANs for Image Editing. [Paper presentation]. Proceedings of NIPS 2016: Annual Conference on Neural Information Processing Systems, pp. 1-9. Barcelona, Spain. https://arxiv.org/pdf/1611.06355.pdf
  • Robinson, J. (2015, October 20). 7 Scenes That Proved Especially Hard to Digitally Create. Vanity Fair. https://www.vanityfair.com/hollywood/2015/10/paul-walker-furious-7-scenes-digitally-recreated
  • Schwartz, O. (2018, November 12). You thought fake news was bad? Deep fakes are where truth goes to die. The Guardian. https://www.theguardian.com/technology/2018/nov/12/deep-fakes-fake-news-truth
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  • Taigman, Y., Polyak, A., Wolf, L. (2017, April 24-27). Unsupervised Cross-Domain Image Generation. [Paper presentation]. ICLR 2017: International Conference on Learning Representations. Toulon, France. https://openreview.net/pdf?id=Sk2Im59ex
  • Valery, P. (1964). The Conquest of Ubiquity (trans. Ralph Manheim). Pantheon Books.
  • Vincent, J. (2018, August 26). Deepfakes for dancing: you can now use AI to fake those dance moves you always wanted. The Verge. https://www.theverge.com/2018/8/26/17778792/deepfakes-video-dancing-ai-synthesis
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The Impact of Artificial Intelligence on Photography and Painting in the Post-Truth Era and the Issues of Creativity and Authorship

Year 2021, Volume: 7 Issue: 2, 243 - 270, 30.12.2021
https://doi.org/10.46641/medeniyetsanat.994950

Abstract

In arts, especially visual arts, humans have perfected their skills to create distinctive experiences by combining a multifaceted interplay between the substance and design of images. Innate mechanisms of this process have remained unknown so far, and no artificial system with similar capabilities exists yet. However, the increasing prevalence of artificial intelligence in arts has drastically changed what seems to be the underlying constants, such as artistic creativity and authorship of artworks. This phenomenon becomes even more commonplace in the post-truth era as facts become fiction in competing versions. Although art has not always been searching for truths, artificial intelligence powered by generative adversarial networks puts the entire concept of art in a much larger context. In such a context, this descriptive-qualitative study based on literature review, which aims to discuss the impacts of artificial intelligence on photography and painting in the post-truth era and the issues of creativity and authorship, first explains the concept of generative adversarial networks and then examines a sample of their uses in photography and painting with concrete examples. Later, the study discusses the effects of artificial intelligence driven by generative adversarial networks on the art market and analyzes the concept of creativity and the issue of authorship because of those impacts in the context of works of art. Finally, the notion of post-truth is explained, and what the advent of artificial intelligence is likely to mean for art in the future within the framework of post-truth is questioned. Results show that the lines between art's expressive and demonstrative functions are beginning to blur, while the border between fiction and reality is becoming increasingly blurred. AI powered by GANs re-contextualizes the meaning of the truth in artistic endeavors as it happens whenever a novel medium or technology appears and is increasingly adopted by more people at various paces and rates.

References

  • Agarwal, S., Farid, H., Gu, Y., He, M., Nagano, K., Li, H. (2019, June 16-20). Protecting World Leaders Against Deep Fakes. [Paper presentation] IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019), pp. 1-8. Long Beach, CA, USA. https://openaccess.thecvf.com/content_CVPRW_2019/papers/Media%20Forensics/Agarwal_Protecting_World_Leaders_Against_Deep_Fakes_CVPRW_2019_paper.pdf
  • Alemoru, K. (2019, March 7). AI artwork flops at auction, robot apocalypse not here yet. Dazed Digital. https://www.dazeddigital.com/art-photography/article/43628/1/klingemannai-ai-auction-first-european-piece-disappointment
  • Antipov, G., Baccouche, M., Dugelay, J.L. (2017, September 17-20). Face aging with conditional generative adversarial networks. [Paper presentation] Proceedings of IEEE International Conference on Image Processing (ICIP), pp. 2089 – 2093. Beijing, China. https://doi.org/10.1109/ICIP.2017.8296650
  • Arendt, H. (1972). Crises of the Republic: Lying in Politics, Civil Disobedience on Violence, Thoughts on Politics, and Revolution. Harcourt Brace Jovanovich.
  • Baudrillard, J. (2020). Simülakrlar ve Simülasyon (trans. Oğuz Adanır). Doğu Batı Yayınları.
  • Benjamin, W. (1969). The Work of Art in the Age of Mechanical Reproduction. In H. Arendt (ed.), Illuminations (pp. 217-251). Schocken Books.
  • Biesecker, B. A. (2018). Toward an Archaeogenealogy of Post-truth. Philosophy & Rhetoric, 51(4), 329-341, https://doi.org/10.5325/philrhet.51.4.0329
  • Boisvert, A. M. (2020, February 15). What Do Machines Want? AI CIAC MTL Magazine. http://ciac.ca/wp-content/uploads/2020/08/IA_QUE-VEULENT-LES-MACHINES_en_web.pdf
  • BuzzFeedVideo. (2018, April 17). You Won’t Believe What Obama Says In This Video! [Video]. YouTube. https://www.youtube.com/watch?v=cQ54GDm1eL0&ab_channel=BuzzFeedVideo
  • Chollet, F. [@fchollet]. (2017, July 13). GANism (the specific look and feel of seemingly GAN-generated images) may yet become a significant modern art trend. [Tweet]. Twitter. https://twitter.com/fchollet/status/885378870848901120
  • Christie’s. (2018, December 12). Is artificial intelligence set to become art’s next medium? https://www.christies.com/features/A-collaboration-between-two-artists-one-human-one-a-machine-9332-1.aspx
  • Dangerfield, K. (2020, December 24). Queen Elizabeth’s deepfake Christmas message a ‘stark warning’. Global News. https://globalnews.ca/news/7540882/queen-elizabeth-deepfake-christmas-message/
  • De Mántaras, R. L. (2017). Artificial Intelligence and the Arts: Toward Computational Creativity. In F. Gonzales (ed.), The Next Step-Exponential Life (pp. 100-124). BBVA & The Open Mind.
  • Elgammal, A. (2018, October 29). What the Art World Is Failing to Grasp about Christie’s AI Portrait Coup. Artsy. https://www.artsy.net/article/artsy-editorial-art-failing-grasp-christies-ai-portrait-coup
  • Elgammal, A., Liu, B., Elhoseiny, M., Mazzone, M. (2017, June 20-22). CAN: Creative Adversarial Networks, Generating "Art" by Learning About Styles and Deviating from Style Norms. [Paper presentation]. Proceedings of 8th International Conference on Computational Creativity (ICCC), pp. 96-103. Atlanta, GA, USA. https://computationalcreativity.net/iccc2017/ICCC_17_accepted_submissions/ICCC-17_paper_47.pdf
  • Feteiha, A. A., (2019, September 23). Artificial Art: How GANs are making machines creative. Heartbeat. https://heartbeat.fritz.ai/artificial-art-how-gans-are-making-machines-creative-b99105627198
  • Gerard, D. (2021, March 19). It’s a $69 Million JPEG, but Is It Art? Foreign Policy. https://foreignpolicy.com/2021/03/19/nft-beeple-69-million-art-crypto-nonfungible-token/
  • Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y. (2014, December 8-13). Generative Adversarial Networks. [Paper presentation]. Proceedings of NIPS 2014: International Conference on Neural Information Processing Systems, pp 2234–2242. Montréal, Canada. https://arxiv.org/pdf/1406.2661.pdf
  • Greshko, M. (2018, May 18). Meet Sophia, the Robot That Looks Almost Human. National Geographic. https://www.nationalgeographic.com/photography/article/sophia-robot-artificial-intelligence-science
  • Heit, H. (2018). “there are no facts”: Nietzsche as Predecessor of Post-Truth?, Studia Philosophica Estonica, 11(1), 44-63. http://dx.doi.org/10.12697/spe.2018.11.1.03
  • Itzkoff, D. (2016, December 27). How ‘Rogue One’ Brought Back Familiar Faces. The New York Times. https://www.nytimes.com/2016/12/27/movies/how-rogue-one-brought-back-grand-moff-tarkin.html
  • Jin, Y., Zhang, J., Li, M., Tian, Y., Zhu, H., Fang, Z. (2017, August 11-13). Towards the Automatic Anime Characters Creation with Generative Adversarial Networks. [Paper presentation]. Comiket 92, pp. 1-16. Tokyo, Japan. https://arxiv.org/pdf/1708.05509.pdf
  • Kinariwala, T. (2019, December 16). Generating Art From Neural Networks. Worldquant. https://www.weareworldquant.com/en/thought-leadership/generating-art-from-neural-networks/
  • Kreitner, R. (2016, November 30). Post-Truth and Its Consequences: What a 25-Year-Old Essay Tells Us About the Current Moment. The Nation. https://www.thenation.com/article/archive/post-truth-and-its-consequences-what-a-25-year-old-essay-tells-us-about-the-current-moment/
  • Kwok, A. O. J., Koh, S. G. M. (2020). Deepfake: a social construction of technology perspective. Current Issues in Tourism, 1-5. https://doi.org/10.1080/13683500.2020.1738357
  • Ledig, C., Theis, L., Huszar, F., Caballero, J., Cunningham, A., Acosta, A., Aitken, A., Tejani A., Totz, J., Wang, Z., Shi, W. (2017, July 21-26). Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. [Paper presentation]. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 105 – 114. Honolulu, HI, USA. https://doi.org/10.1109/CVPR.2017.19
  • Lee, D. (2019, May 19). Deepfake Salvador Dalí takes selfies with museum visitors. The Verge. https://www.theverge.com/2019/5/10/18540953/salvador-dali-lives-deepfake-museum
  • Lyons, K. (2020, January 20). FTC says the tech behind audio deepfakes is getting better. The Verge. https://www.theverge.com/2020/1/29/21080553/ftc-deepfakes-audio-cloning-joe-rogan-phone-scams
  • Lyotard, J. F. (2013). Postmodern Durum (trans. Ahmet Çiğdem). Bilgesu Yayınları.
  • McIntyre, L. C. (2018). Post-truth. MIT Press.
  • Morris, I. (2018, February 5). Revenge 'Porn' Gets Even More Horrifying With Deepfakes. Forbes. https://www.forbes.com/sites/ianmorris/2018/02/05/fakeapp-allows-anyone-to-make-deepfake-porn-of-anyone/?sh=d4dd09c391c9
  • Naumann, F. M. (2012). The Recurrent, Haunting Ghost: Essays on the Art, Life and Legacy of Marcel Duchamp. Readymade Press.
  • Nicholson, C. (2020). A Beginner's Guide to Generative Adversarial Networks (GANs). Pathmind. https://wiki.pathmind.com/generative-adversarial-network-gan
  • O’Neil, L. (2019, June 12). Doctored video of sinister Mark Zuckerberg puts Facebook to the test. The Guardian. https://www.theguardian.com/technology/2019/jun/11/deepfake-zuckerberg-instagram-facebook
  • Oxford Languages. (2016). Word of the Year 2016. https://languages.oup.com/word-of-the-year/2016/
  • Oxford Learner’s Dictionaries. (2021). Post-truth. In Oxford Learner’s Dictionaries.com dictionary. https://www.oxfordlearnersdictionaries.com/definition/english/post-truth?q=post-truth
  • Paris, B., Donovan, J. (2019). Deepfakes and Cheap Fakes: The Manipulation of Audio and Visual Evidence. Data & Society. https://datasociety.net/wp-content/uploads/2019/09/DS_Deepfakes_Cheap_FakesFinal-1-1.pdf
  • Parkin, S. (2019, June 22). ‘Politicians fear this like fire’. The Guardian. https://www.theguardian.com/technology/ng-interactive/2019/jun/22/the-rise-of-the-deepfake-and-the-threat-to-democracy
  • Perarnau, G., Van de Weijer, J., Raducanu, B., Álvarez, J. M. (2016, December 5-10). Invertible Conditional GANs for Image Editing. [Paper presentation]. Proceedings of NIPS 2016: Annual Conference on Neural Information Processing Systems, pp. 1-9. Barcelona, Spain. https://arxiv.org/pdf/1611.06355.pdf
  • Robinson, J. (2015, October 20). 7 Scenes That Proved Especially Hard to Digitally Create. Vanity Fair. https://www.vanityfair.com/hollywood/2015/10/paul-walker-furious-7-scenes-digitally-recreated
  • Schwartz, O. (2018, November 12). You thought fake news was bad? Deep fakes are where truth goes to die. The Guardian. https://www.theguardian.com/technology/2018/nov/12/deep-fakes-fake-news-truth
  • Stoker, G. (2017). Why Politics Matters: Making Democracy Work. Palgrave Macmillan.
  • Taigman, Y., Polyak, A., Wolf, L. (2017, April 24-27). Unsupervised Cross-Domain Image Generation. [Paper presentation]. ICLR 2017: International Conference on Learning Representations. Toulon, France. https://openreview.net/pdf?id=Sk2Im59ex
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There are 51 citations in total.

Details

Primary Language English
Journal Section Makaleler
Authors

İsmail Erim Gülaçtı 0000-0002-6786-479X

Mehmet Emin Kahraman 0000-0002-2089-3067

Publication Date December 30, 2021
Acceptance Date December 24, 2021
Published in Issue Year 2021 Volume: 7 Issue: 2

Cite

APA Gülaçtı, İ. E., & Kahraman, M. E. (2021). The Impact of Artificial Intelligence on Photography and Painting in the Post-Truth Era and the Issues of Creativity and Authorship. Medeniyet Sanat Dergisi, 7(2), 243-270. https://doi.org/10.46641/medeniyetsanat.994950


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