The Impact of Artificial Intelligence and Machine Learning on Contemporary Photography Practices

Year 2023, , 274 - 289, 01.08.2023

Atila Işık

https://doi.org/10.58850/bodrum.1283006

Abstract

In the 21st century, the development of communication and digital devices has led to new production approaches in visual arts. Today, photography has become digitally editable and synthetically produced with the help of artificial intelligence. The primary aim of the study is to examine the role of artificial intelligence, one of the most recent technologies instrumentalized in photography practices, in the development of the field by discussing its contributions in terms of size and quality. The scope of the study includes the areas of use of artificial intelligence in contemporary photography applications and the positive and negative aspects of its effects in these areas. In the study, which aims to examine from which perspectives artificial intelligence applications in photography, one of the important branches of visual art, can be handled, it was determined that there are many different application areas. In the article, beyond the definition of “artificial intelligence photography”, it is tried to reveal how artificial intelligence and photography practice are concretely related in different application stages for a photographer. The qualitative method based on the descriptive model was applied as the research method in the study. During the research process, visual and textual data obtained from literature review, visual readings and source scans were evaluated, and the findings obtained were included in the content in a way to contribute. As a result, it was seen that photography has a technically intricate structure with many sub-headings in the context of different methods, orientations and techniques. When this structure was analyzed in depth, it was revealed that artificial intelligence affects the field of photography in both positive and negative ways.

Keywords

Digital Photography, Artificial Intelligence, Machine Learning, Deepfake

Yapay Zekâ ve Makine Öğreniminin Güncel Fotoğraf Uygulamalarına Etkisi

Abstract

21. yüzyılda iletişimin ve dijital aygıtların gelişimi görsel sanatlarda yeni üretim anlayışlarını doğurmuştur. Günümüzde fotoğraf yapay zekâ yardımı ile dijital olarak düzenlenebilen, sentetik ortamda üretilebilen bir hale gelmiştir. Çalışmanın birincil amacı fotoğraf uygulamalarında araçsallaştırılan en güncel teknolojilerden biri olan yapay zekâ uygulamalarının alanın gelişimindeki rolünü sağladığı katkıları boyut ve nitelik bağlamında tartışarak incelemektir. Çalışmanın kapsamı yapay zekânın çağdaş fotoğraf uygulamalarındaki kullanılma alanlarını ve bu alanlardaki etkilerinin olumlu ve olumsuz yönlerden incelenmesini içermektedir. Görsel sanatın önemli dallarından biri olan fotoğrafta yapay zekâ uygulamalarının, hangi perspektiflerden ele alınabileceğini de incelemeyi amaçlayan çalışmada pek çok farklı uygulama alanının olduğu tespit edilmiştir. Makalede bir “yapay zekâ fotoğrafçılığı” tanımından öte uygulama açısından yapay zekâ ile fotoğraf pratiğinin bir fotoğrafçı açısından farklı uygulama aşamalarında somut olarak nasıl ilişkilendiği ortaya konulmaya çalışılmıştır. Çalışmada araştırma yöntemi olarak betimsel modele dayalı nitel yöntem uygulanmıştır. Araştırma sürecinde literatür incelemesi, imgelem okumaları ve kaynak taramalarından elde edilen görsel ve metinsel veriler değerlendirilmiş, elde edilen bulgular katkı sağlayacak şekilde içeriğe dâhil edilmiştir. Sonuçta fotoğrafın farklı yöntemler, yönelimler ve teknikler bağlamında pek çok alt başlık barındıran, teknik açıdan girift bir yapısı olduğu görülmüştür. Bu yapı derinlemesine incelendiğinde, yapay zekânın fotoğrafçılık alanını hem olumlu hem de olumsuz açılardan etkilediği ortaya çıkmıştır.

Keywords

Dijital Fotoğraf, Yapay Zekâ, Makine Öğrenimi, Deepfake

References

• À perte de vue. (t.y.). Faire voir ce qu’ils ne peuvent plus voir. À perte de vue. https://www.apertedevue.org/ (23.05.2023).
• Abreu, C. M. (2023, 21 Mart). Vladimir Putin’s recent schedule fuels false claims on social media. France24. https://www.france24.com/en/tv-shows/truth-or-fake/20230321-vladimir-putin-s-recent-agenda-fuels-fake-claims-on-social-media (23.05.2023).
• Acar, M. (2023, 17 Nisan). Midjourney AI komutları ile görsel oluşturma rehberi. Thinpo. https://thinpo.com/midjourney-ai-komutlari-ile-gorsel-olusturma-rehberi/ (23.05.2023).
• Adams, A. (1935). Making a photograph: An introduction to photography. The Studio Ltd.
• Adobe (t.y.). Adobe Firefly ile Dream Bigger. Adobe. https://www.adobe.com/tr/sensei/generative-ai/firefly.html (21.07.2023).
• Akbaş, F., Korkmazgil, G. (2010). Dijital dünyada fotoğraf. Say Yayınevi.
• Apple. (2017). The future is here: iPhone X. Apple Newsroom. https://www.apple.com/newsroom/2017/09/the-future-is-here-iphone-x/ (23.05.2023).
• Bonanata, A. (2023, 21 Mart). Il fake della foto di Putin inginocchiato ai piedi di xi e i rischi dell’intelligenza artificiale. RaiNews. https://www.rainews.it/articoli/2023/03/fake-foto-putin-inginocchiato-piedi-xi-jinping-rischi-intelligenza-artificiale-9db959c8-8eab-4bff-bbcf-f69863065cee.html (23.05.2023).
• Böcekler, A. G. B. (2013). Magnum fotoğraf ajansı’nda foto-manipülasyon: Martin Parr örneği. I. Uluslararası Sanat Sempozyumu Bildiriler Kitabı (137-144). Sakarya Üniversitesi Güzel Sanatlar Fakültesi Yayınları. https://stmf.sakarya.edu.tr/sites/stmf.sakarya.edu.tr/file/1385683148-ustm-pdf.pdf (07.25.2023).
• Burt, T. (2020,1 Eylül). New steps to combat disinformation. Microsoft Blog. https://blogs.microsoft.com/on-the-issues/2020/09/01/disinformation-deepfakes-newsguard-video-authenticator/ (01.04.2023).
• Childs, M. (2011, 1 Kasım). John McCarthy: Computer scientist known as the father of AI. Independent UK. https://www.independent.co.uk/news/obituaries/john-mccarthy-computer-scientist-known-as-the-father-of-ai-6255307.html (23.05.2023).
• Constant, N. (t.y.). AI photography: How is AI changing the world of photography? Expert Photography. https://expertphotography.com/ai-photography/ (01.04.2023).
• Edwards, B. (2023, 21 Şubat). Viral Instagram photographer has a confession: His photos are AI-generated. Ars Technica. https://arstechnica.com/information-technology/2023/02/viral-instagram-photographer-has-a-confession-his-photos-are-ai-generated/ (01.04.2023).
• Galal, A. M. (2016). An analytical study on the modern history of digital photography. International Design Journal, 6(2), 203-215.
• Garling, W. (2023, 17 Ocak). How to identify an AI-generated image: 4 ways. Makeuseof. https://www.makeuseof.com/how-to-identify-ai-generated-image/ (01.04.2023).
• Gershgorn, D. (2017, 26 Temmuz). The data that transformed AI research—and possibly the world. Quartz. https://qz.com/1034972/the-data-that-changed-the-direction-of-ai-research-and-possibly-the-world (23.05.2023).
• Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., ... & Bengio, Y. (2020). Generative adversarial networks. Communications of the ACM, 63(11), 139-144.
• Growcoot, M. (2023, 28 Şubat). Exclusive: Vogue photographer admits some of his images are AI. Petapixel. https://petapixel.com/2023/02/28/exclusive-vogue-photographer-admits-some-of-his-images-are-ai/ (23.05.2023).
• Laratta, A. (2023, 20 Nisan). Debate rages over photographer who wins contest with a photo of artificial intelligence. Finestre sull’Arte. https://www.finestresullarte.info/en/news/debate-rages-over-photographer-who-wins-contest-with-a-photo-of-artificial-intelligence (23.05.2023).
• Martin, M. (2019, Ocak 19). Fstoppers reviews the Arsenal smart camera assistant: A must have accessory? Fstoppers. https://fstoppers.com/apps/fstoppers-reviews-arsenal-smart-camera-assistant-must-have-accessory-327265 (23.05.2023).
• McCarthy, J. (2007). What is artificial intelligence? Stanford University Computer Science Department. http://jmc.stanford.edu/articles/whatisai/whatisai.pdf (01.04.2023).
• McCorduck, P. (1991). AARONS’s code: Meta-art. Artificial intelligence, and the work of Harold Cohen. H. Freeman and Company.
• Özkeçeci, İ., Çiçek, E. (2017). Fotoğraf sanat ilişkisi bağlamında görsel tasarım öğelerinin sanat eserini oluşturmadaki rolü. Art-Sanat Dergisi, (7), 309-319.
• OpenAI (t.y.). DALL·E 2. OpenAI. https://openai.com/dall-e-2 (21.7.2023).
• Poltronieri, F. A., Hänska, M. (2019). Technical images and visual art in the era of artificial intelligence: From GOFAI to GANs. Proceedings of the 9th International Conference on Digital and Interactive Arts. https://doi.org/10.1145/3359852.3359865
• Poole, D. I., Goebel, R. G., & Mackworth, A. K. (1998). Computational intelligence (Vol. 1). Oxford University Press. Romano, Y., Isidoro, J., & Milanfar, P. (2016). RAISR: rapid and accurate image super resolution. IEEE Transactions on Computational Imaging, 3(1), 110-125. https://doi.org/10.1109/TCI.2016.2629284
• Rtology, E. (2023, 3 Mayıs). Midjourney’s latest version 5.1 AI art generator. The V5.1 image system is here! Medium. https://medium.com/mlearning-ai/midjourneys-latest-version-5-1-ai-art-generator-the-v5-1-image-system-is-here-db8faa378876 (23.05.2023).
• Rubinstein, D., Golding, J., Fisher, A. (2013). On the verge of photography: Imaging beyond representation. Article Press.
• Samuel, A. L. (1959). Some studies in machine learning using the game of checkers. IBM Journal of research and development, 3(3), 210-229.
• Say, C. (2018). 50 soruda yapay zekâ. 7 Renk Basım Yayın ve Filmcilik.
• Schwent, P. (2021, 7 Aralık). Google’s Magic Eraser vs. Samsung’s Object Eraser [Video] https://www.youtube.com/watch?v=oW-poyTr34Y&ab_channel=RandoTechInfo (05.04.2023).
• Shen, C., Kasra, M., Pan, W., Bassett, G. A., Malloch, Y., & O’Brien, J. F. (2019). Fake images: The effects of source, intermediary, and digital media literacy on contextual assessment of image credibility online. New media & society, 21(2), 438-463. https://doi.org/10.1177/1461444818799526
• Singh, G., Mittal, A., & Aggarwal, N. (2020). ResDNN: deep residual learning for natural image denoising. IET Image Processing, 14(11), 2425-2434. https://doi.org/10.1049/iet-ipr.2019.0623
• Sucu, İ. Ataman, E. (2020). Dijital evrenin yeni dünyası olarak yapay zeka ve her filmi üzerine bir çalışma. Yeni Medya Elektronik Dergisi, 4(1), 40-52.
• Tatsuno, K. (2006). Current trends in digital cameras and camera-phones. Science & Technology Trends Quarterly Review, (18), 35-44.
• Terranova, A. (2023, 26 Nisan). How AI imagery is shaking photojournalism. Blind Magazine. https://www.blind-magazine.com/stories/how-ai-imagery-is-shaking-photojournalism/ (05.05.2023).
• Tolosana, R., Vera-Rodriguez, R., Fierrez, J., Morales, A., & Ortega-Garcia, J. (2020). Deepfakes and beyond: A survey of face manipulation and fake detection. Information Fusion, 64, 131-148.
• Topçuoğlu, N. (2010). Fotoğraf ölmedi ama tuhaf kokuyor. Yapı Kredi Yayınları.
• Turan, E. (2013). Analog ve dijital duyarkatların yapısal özellikleri. Alfa Yayınları.
• Vachhani, P. (2016, 12 Nisan). DeepArt When Mathematics Meets Art. Medium. https://medium.com/way2do-p/deepart-f977463c8034 (05.05.2023).
• Vincent, J. (2023, 17 Ocak). Getty Images is suing the creators of AI art tool Stable Diffusion for scraping its content. The Verge. https://www.theverge.com/2023/1/17/23558516/ai-art-copyright-stable-diffusion-getty-images-lawsuit (05.04.2023).
• Waisbord, S. (2018). Truth is what happens to news: On journalism, fake news, and post-truth. Journalism Studies, 19(13), 1866-1878. https://doi.org/10.1080/1461670X.2018.1492881
• Weber, J. (2023, 23 Mart). Fact check: No, Putin did not kneel before Xi Jinping. Deutsche Welle. https://www.dw.com/en/fact-check-no-putin-did-not-kneel-before-xi-jinping/a-65099092 (05.05.2023).
• Wynants, N., Reijnen, L., & Brinkman, E. (2020). When fact is fiction: Documentary art in the post-truth era. Antennae-Arts in Society.
• Yaykın, M. (2010). Fotoğraf ideolojisi. Kalkedon Yayıncılık.
• Zhang, K., Zuo, W., Chen, Y., Meng, D., & Zhang, L. (2017). Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising. IEEE transactions on image processing, 26(7), 3142-3155. https://doi.org/10.1109/TIP.2017.2662206