The Impact of AI on Transforming Concepts in Contemporary Photography

Authors

  • Maryam M. Hassan Department of Photography, Cinema and Television, Faculty of Applied Arts, 6th October University, Egypt

DOI:

https://doi.org/10.25038/am.v0i28.613

Keywords:

photography; GAN; authenticity; artificial intelligence; AICAN.

Abstract

The integration of AI, particularly deep learning, has significantly altered the landscape of photography, offering tools that redefine workflows and expand creative horizons. AI enables photographers to create new images and manipulate existing ones, thereby pushing the boundaries of artistic expression. However, this capability also raises concerns about the blurring of lines between authorship and originality. This research investigates AI's impact on traditional photography, with a focus on creativity and authorship, particularly through technologies like GANs and AICAN. The study examines how AI-generated images challenge the distinction between reality and fiction, influencing the art and reshaping concepts of creativity in AI-produced works. As the distinction between truth and falsehood becomes increasingly blurred in a world of misinformation, the research explores AI’s role in deepening this crisis. The research problem centers on the need to re-evaluate the role of photographers as AI takes over many photographic tasks, raising questions about how this technology redefines artistic creativity, authenticity, and authorship. The study questions whether artistic vision and the human touch will remain crucial or if the focus will shift toward collaborative creativity between humans and AI. The significance of this research lies in its ability to provide insights into AI’s impact on photography, helping navigate the future of this art form. This research aims to analyze the artistic and expressive qualities of concrete examples of artificial intelligence applications in photography, as well as to deconstruct the concepts of art, creativity, authorship, and authenticity in photographic artworks considering modern technology.

Author Biography

Maryam M. Hassan, Department of Photography, Cinema and Television, Faculty of Applied Arts, 6th October University, Egypt

Maryam Hassan, Cairo, an Associate Professor at the Faculty of Applied Arts, 6th October University. She earned her Ph.D. in Applied Arts (Cinema) from Helwan University, with the dissertation “The Role of Modern Technologies in the Quality of 3D Cinematic Image Production to Develop Cinematic Language” (2011–2015). She also holds a master’s degree in (Photography and Cinema) and a Graduate Diploma in Art Therapy. She focuses on the history of images, their role in visual culture and identity, and their social and psychological impact. She has held several solo exhibitions in Egypt and Europe. She has received numerous awards in photography and participated in international exhibitions, including the Sarajevo International Festival, the Revolution Festival in Tunisia, and the Mediterranean Youth Biennale. She also won prizes in various art salons such as the Nile Salon and the Youth Salon and was awarded a grant from the Cultural Resource Foundation in Brussels.

References

Adorama. “The Impact of AI–Generated Art on Photography & Creative Pursuits | Master Your Craft.” 2022. YouTube. https://www.youtube.com/watch?v=h0yKcyWHf1I&t=17s.

Ballester, Omar. “An Artificial Intelligence Definition and Classification Framework for Public Sector Applications.” In DG.O2021: The 22nd Annual International Conference on Digital Government Research, 67–75. Association for Computing Machinery, 2021. https://doi.org/10.1145/3463677.3463709. DOI: https://doi.org/10.1145/3463677.3463709

Bhattacharjee, Govind. “Art and Photography in the Age of Artificial Intelligence.” In 12th International Photographic Conference of PAD. Kolkata, 2023.

CBS News. “AI ‘Nudify’: The Impact, Law Changes, and the Fight.” Last modified December 24, 2023. Accessed January 3, 2025. https://www.cbsnews.com/news/ai-nudify-impacts-law-change-fight-60-minutes/.

Chen, Yongcai. “Artificial Intelligence Technology in Photography and Future Challenges and Reflections.” The Frontiers of Society, Science and Technology 6, no. 6 (2024): 24–30. https://doi.org/10.25236/FSST.2024.060605. DOI: https://doi.org/10.25236/FSST.2024.060605

Elgammal, Ahmed, Bingchen Liu, Mohamed Elhoseiny, and Marian Mazzone. “CAN: Creative Adversarial Networks, Generating ‘Art’ by Learning About Styles and Deviating from Style Norms.” In Proceedings of ICCC, Atlanta, 2017. https://doi.org/10.48550/arXiv.1706.07068.

Gatys, Leon A., Alexander S. Ecker, and Matthias Bethge. “A Neural Algorithm of Artistic Style.” Journal of Vision, 16, no. 12 (2016): 1–16. https://doi.org/10.48550/arXiv.1508.06576. DOI: https://doi.org/10.1167/16.12.326

Glynn, Paul. “Sony World Photography Award 2023: Winner Refuses Award After Revealing AI Creation.” BBC News. April 18, 2023. https://www.bbc.com/news/entertainment-arts-65296763.

Gray, Jeremy. “‘Deep Nostalgia’ AI Tech Animates Old Photos and Brings Them to Life.” March 1, 2021. Digital Photography Review. https://www.dpreview.com/news/4889126219/deep-nostalgia-ai-tech-animates-old-photos-and-brings-them-to-life.

Grimsley, Reese. “Edge AI: Real-Time Face Detection and Recognition.” Texas Instruments, 2023. Accessed April 6, 2025, https://www.ti.com/lit/wp/sprad74/sprad74.pdf.

Gülaçtı, İsmail Erim, and Mehmet Emin Kahraman. “The Impact of Artificial Intelligence on Photography and Painting in the Post–Truth Era and the Issues of Creativity and Authorship.” Medeniyet Sanat – İMÜ Sanat Tasarım ve Mimarlık Fakültesi Dergisi 7, no. 2 (2021): 243–70. https://doi.org/10.46641/medeniyetsanat.994950. DOI: https://doi.org/10.46641/medeniyetsanat.994950

Hays, James, and Alexei Efros. “Scene Completion Using Millions of Photographs.” Computer Graphics Proceedings, Annual Conference Series, 2007, 1–9. DOI: https://doi.org/10.1145/1275808.1276382

kail9974. “[논문 리뷰] HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color Histograms (CVPR 2021).” August 31, 2021. Chill. https://re-chill.tistory.com/entry/HistoGAN.

Kili. “Programming Image Classification with Machine Learning: Why and How?” Accessed April 6, 2025. https://kili-technology.com/data-labeling/computer-vision/image-annotation/programming-image-classification-with-machine-learning.

Lister, Martin. “Photography in the Age of the Electronic Image.” In Photography: A Critical Introduction, edited Liz Wells, 313–400. John Libbey and Co Ltd., 2006.

Mazzone, Marian, and Ahmed Elgammal. “Art, Creativity, and the Potential of Artificial Intelligence.” Arts 8, no. 26 (2019): 1–9. https://doi.org/10.3390/arts8010026. DOI: https://doi.org/10.3390/arts8010026

Nicholson, Chris V. “A Beginner's Guide to Generative Adversarial Networks (GANs).” Pathmind, 2020. https://wiki.pathmind.com/generative-adversarial-network-gan

Ozen, Emre, Fikret Alim, Sefa Burak Okcu, Enes Kavakli, and Cevahir Cigla. “Real–Time Face Recognition System at the Edge.” In Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII, edited by Ivan Kadar, Erik P. Blasch, Lynne L. Grewe, Proc. of SPIE Vol. 13057, 2024. https://doi.org/10.1117/12.3013671. DOI: https://doi.org/10.1117/12.3013671

Russon, Mary-Ann. “Google DeepDream robot: 10 Weirdest Images Produced by AI 'Inceptionism' and Users Online.” International Business Times. July 6, 2015. https://www.ibtimes.co.uk/google-deepdream-robot-10-weirdest-images-produced-by-ai-inceptionism-users-online-1509518.

Schneider, Jaron. “State of Photography: Business Isn’t Great and Use of AI Is Going Up.” April 20, 2023. PetaPixel. https://petapixel.com/2023/04/20/2023-state-of-photography-business-isnt-great-and-use-of-ai-is-going-up/.

Stiegler, Bernard. Nanjing Lectures: Reading Marx and Engels in the Human Record–From “The German Ideology” to “Dialectics of Nature”. Translated by Zhang Fugong. Nanjing University Press, 2019.

Tang, Zeyu. “The Transformation of Photography by Artificial Intelligence Generative AI Technology.” Journal of Artificial Intelligence Practice 6 (2023): 57–62. https://doi.org/10.23977/jaip.2023.060809. DOI: https://doi.org/10.23977/jaip.2023.060809

Wei, Lei. “Legal Risk and Criminal Imputation of Weak Artificial Intelligence.” In IOP Conference Series: Materials Science and Engineering 490, no. 6 (2019): 062085. https://doi.org/10.1088/1757-899X/490/6/062085. DOI: https://doi.org/10.1088/1757-899X/490/6/062085

Yi, Ran, Yong-Jin Liu, Yu-Kun Lai, and Paul L. Rosin. “Generating Artistic Portrait Drawings from Face Photos with Hierarchical GANs.” In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR ‘19), 10735–10744. Long Beach, CA, USA, 2019. DOI: 10.1109/CVPR.2019.01100 DOI: https://doi.org/10.1109/CVPR.2019.01100

Zakharov, Egor, Aliaksandra Shysheya, Egor Burkov, and Victor Lempitsky. “Few-Shot Adversarial Learning of Realistic Neural Talking Head Models. [Paper presentation].” Proceedings of IEEE/CVF International Conference on Computer Vision (ICCV). Seoul, South Korea, 2019, 9459–68. https://doi.org/10.1109/ICCV.2019.00955. DOI: https://doi.org/10.1109/ICCV.2019.00955

Zhang, Kai, Wangmeng Zuo, Yunjin Chen, Deyu Meng, and Lei Zhang. “Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising.” IEEE Transactions on Image Processing 26, no. 7 (2017): 3142–55. https://doi.org/10.1109/TIP.2017.2662206. DOI: https://doi.org/10.1109/TIP.2017.2662206

Zhang, Michael. “Henri Cartier-Bresson on ‘The Decisive Moment’.” Peta Pixel. March 12. 2020. https://petapixel.com/2012/03/20/henri-cartier-bresson-on-the-decisive-moment/.

Zhu, Jun-Yan, Taesung Park, Phillip Isola, and Alexei A. Efros, “Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks. [Paper presentation].” Proceedings of 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy, 2017, 2242–51. https://doi.org/10.1109/ICCV.2017.244. DOI: https://doi.org/10.1109/ICCV.2017.244

Published

15.04.2025

How to Cite

M. Hassan, M. (2025). The Impact of AI on Transforming Concepts in Contemporary Photography. AM Journal of Art and Media Studies, (36). https://doi.org/10.25038/am.v0i28.613

Issue

Section

MAIN TOPIC: Critical Theory, Media, and Education in the Era of Artificial Intelligence