The Ontology of Cinema in the Age of Generative Artificial Intelligence: A Manifesto in Defending the Human Footprint

Öz

This study examines the integration of generative artificial intelligence technologies into cinema and audiovisual media production not merely as a technical innovation or an issue of industrial efficiency, but as a crisis that transforms the ontological, aesthetic, ethical, and labour-political foundations of cinema. The aim of the study is not to produce a simple anti-technological stance against artificial intelligence, but to defend cinema’s relationship with the human body, testimony, error, creative risk, and ethical responsibility. In this regard, André Bazin’s ontology of the photographic image, Vivian Sobchack’s film phenomenology, Stanley Cavell’s reflections on cinema, auteur theory, studies on algorithmic bias, and contemporary debates on creative labour are evaluated together. Methodologically, the study adopts qualitative theoretical synthesis and critical discourse analysis. In addition, the artificial intelligence provisions in the 2023 agreements of the WGA and SAG-AFTRA, as well as current text-to-video generative models, are included in the contextual framework of the study. The study concludes that a smooth and optimized mode of visual production devoid of human error, bodily vulnerability, lived experience, and artistic risk is not cinema itself, but an algorithmic simulation of cinema.

Anahtar Kelimeler

• Generative artificial intelligence
• cinema ontology
• actor’s body
• algorithmic auteur
• creative labour.

Üretken Yapay Zekâ Çağında Sinemanın Ontolojisi: İnsan İzini Savunma Manifestosu

Öz

Bu çalışma, üretken yapay zekâ teknolojilerinin sinema ve görsel-işitsel medya üretim süreçlerine dâhil oluşunu yalnızca teknik bir yenilik ya da endüstriyel verimlilik meselesi olarak değil, sinemanın ontolojik, estetik, etik ve emek-politik temellerini dönüştüren bir kriz alanı olarak ele almaktadır. Çalışmanın amacı, yapay zekâya karşı basit bir teknoloji karşıtlığı üretmek değil; sinemanın insan bedeni, tanıklık, hata, yaratıcı risk ve etik sorumlulukla kurduğu bağı savunmaktır. Bu doğrultuda André Bazin’in fotoğrafik görüntü ontolojisi, Vivian Sobchack’in film fenomenolojisi, Stanley Cavell’in sinema düşüncesi, auteur kuramı, algoritmik önyargı çalışmaları ve güncel yaratıcı emek tartışmaları birlikte değerlendirilmiştir. Yöntem olarak nitel kuramsal sentez ve eleştirel söylem analizi benimsenmiştir. Ayrıca WGA ve SAG-AFTRA’nın 2023 sözleşmelerindeki yapay zekâ hükümleri, metinden-videoya üretim yapan güncel modeller çalışmanın bağlamına dâhil edilmiştir. Çalışma, insan hatasından, bedensel kırılganlıktan, yaşanmışlıktan ve sanatsal riskten yoksun pürüzsüzleştirilmiş görsel üretimin sinema değil, sinemanın algoritmik bir simülasyonu olduğu sonucuna ulaşmaktadır.

Anahtar Kelimeler

• Üretken yapay zekâ
• sinema ontolojisi
• oyuncu bedeni
• algoritmik auteur
• yaratıcı emek.

Kaynakça

1. Kaynakça Astruc, A. (2013). The birth of a new avant-garde: La caméra-stylo. In T. Corrigan, P. White, & M. Mazaj (Eds.), Critical visions in film theory: Classic and contemporary readings (pp. 603–608). Bedford/St. Martin’s. Original work published 1948. https://doi.org/10.1525/9780520957411-170
2. Baudrillard, J. (1994). Simulacra and simulation (S. F. Glaser, Trans.). University of Michigan Press. Original work published 1981.
3. Bazin, A. (2005). The ontology of the photographic image. In What is cinema? Volume I (H. Gray, Trans., pp. 9–16). University of California Press. https://doi.org/10.1525/9780520931251-004
4. Beguš, N. (2025). Experimental narratives: A comparison of human crowdsourced storytelling and AI storytelling. Humanities and Social Sciences Communications, 11, Article 1392. https://doi.org/10.1057/s41599-024-03868-8
5. Bender, S. (2025). Generative-AI, the media industries, and the disappearance of human creative labour. Media Practice and Education, 26(2), 200–217. https://doi.org/10.1080/25741136.2024.2355597
6. Bomba, F., & De Angeli, A. (2025). Agency and authorship in AI art: Transformational practices for epistemic troubles. International Journal of Human-Computer Studies, 205, Article 103652. https://doi.org/10.1016/j.ijhcs.2025.103652
7. Brodherson, M., Wrubel, A., & Vickers, J. (2025, November 19). How AI could reinvent film and TV production. McKinsey & Company. https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/tech-forward/how-ai-could-reinvent-film-and-tv-production
8. Brookes, G. (2025). Truth claims and trace: The autographic witness in the algorithm. Memory, Mind & Media, 4, Article e21. https://doi.org/10.1017/mem.2025.15

9. Buolamwini, J. (2019, February 7). Artificial intelligence has a problem with gender and racial bias. Here’s how to solve it. Time. https://time.com/5520558/artificial-intelligence-racial-gender-bias/
10. Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. Proceedings of Machine Learning Research, 81, 77–91. https://proceedings.mlr.press/v81/buolamini18a.html
11. Cavell, S. (1979). The world viewed: Reflections on the ontology of film (Enlarged ed.). Harvard University Press.
12. Cinelytic. (2026). Built for a better film business. https://www.cinelytic.com/
13. Cinelytic. (2026). Platform. https://www.cinelytic.com/platform/
14. Couldry, N., & Mejias, U. A. (2018). Data colonialism: Rethinking big data’s relation to the contemporary subject. Television & New Media, 20(4), 336–349. https://doi.org/10.1177/1527476418796632
15. Deleuze, G. (1989). Cinema 2: The time-image (H. Tomlinson & R. Galeta, Trans.). University of Minnesota Press. Original work published 1985.
16. Google DeepMind. (2026). Veo. https://deepmind.google/models/veo/
17. Google DeepMind. (2026). How to create effective prompts with Veo 3. https://deepmind.google/models/veo/prompt-guide/
18. Hesmondhalgh, D. (2019). The cultural industries (4th ed.). Sage.
19. Jääskeläinen, P., Sharma, N. K., Pallett, H., & Åsberg, C. (2025). Intersectional analysis of visual generative AI: The case of stable diffusion. AI & Society, 40(6), 4341–4362. https://doi.org/10.1007/s00146-025-02207-y
20. Kantayya, S. (Director). (2020). Coded Bias [Film]. 7th Empire Media.
21. Karras, T., Laine, S., & Aila, T. (2019). A style-based generator architecture for generative adversarial networks. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 4401–4410). IEEE. https://doi.org/10.1109/CVPR.2019.00453
22. Kling AI. (2026). Kling VIDEO 3.0 omni model user guide. https://kling.ai/quickstart/klingai-video-3-omni-model-user-guide
23. Koren, L. (1994). Wabi-sabi for artists, designers, poets & philosophers. Stone Bridge Press.
24. Lacan, J. (1998). The four fundamental concepts of psycho-analysis (A. Sheridan, Trans.). W. W. Norton.
25. Lanzmann, C. (Director). (1985). Shoah [Film]. Les Films Aleph.
26. Menkman, R. (2011). The glitch moment(um). Institute of Network Cultures. https://networkcultures.org/_uploads/NN%234_RosaMenkman.pdf
27. Merleau-Ponty, M. (2012). Phenomenology of perception (D. A. Landes, Trans.). Routledge. Original work published 1945.
28. Nieborg, D. B., & Poell, T. (2018). The platformization of cultural production: Theorizing the contingent cultural commodity. New Media & Society, 20(11), 4275–4292. https://doi.org/10.1177/1461444818769694
29. Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York University Press. https://www.jstor.org/stable/j.ctt1pwt9w5
30. O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown.
31. Oltermann, P. (2025, February 18). ‘The most important thing was getting to the truth’: How Claude Lanzmann broke all the rules to create Shoah. The Guardian. https://www.theguardian.com/film/2025/feb/18/the-most-important-thing-was-getting-to-the-truth-how-claude-lanzmann-broke-all-the-rules-to-create-shoah
32. OpenAI. (2024a, Aralık, 9). Sora is here. https://openai.com/index/sora-is-here/
33. OpenAI. (2024b, Aralık, 9). Sora system card. https://openai.com/index/sora-system-card/
34. Pallero, J. (2024, June 27). To err is human: Ideals of perfection in the age of artificial intelligence. Medium. https://medium.com/@javierpallero/to-err-is-human-ideals-of-perfection-in-the-age-of-artificial-intelligence-4836a3f1da9b
35. Runway. (2025). Runway Gen-4: AI video generation with world consistency. https://runwayml.com/research/introducing-runway-gen-4
36. SAG-AFTRA. (2023a, July 17). We’re fighting for the survival of our profession. https://www.sagaftra.org/were-fighting-survival-our-profession
37. SAG-AFTRA. (2023b). Digital replicas. https://www.sagaftra.org/sites/default/files/sa_documents/DigitalReplicas.pdf
38. SAG-AFTRA. (2023c). TV/Theatrical Contracts 2023. https://www.sagaftra.org/contracts-industry-resources/contracts/2023-tvtheatrical-contracts
39. Sarris, A. (1962). Notes on the auteur theory in 1962. Film Culture, 27, 1–8.
40. ScriptBook. (2026). Hard science. Better content. https://www.scriptbook.io/
41. Sobchack, V. (1992). The address of the eye: A phenomenology of film experience. Princeton University Press.
42. Sobchack, V. (2004). Carnal thoughts: Embodiment and moving image culture. University of California Press.
43. Srinivasan, R., & Uchino, K. (2021). Biases in generative art: A causal look from the lens of art history. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (pp. 41–51). Association for Computing Machinery. https://doi.org/10.1145/3442188.3445869
44. Sui, Z., & Wang, S. (2025). Dogme 25: Media primitivism and new auteurism in the age of artificial intelligence. Frontiers in Communication, 10, Article 1659731. https://doi.org/10.3389/fcomm.2025.1659731 United States Holocaust Memorial Museum. (n.d.). Franz Suchomel. Claude Lanzmann Shoah Collection. https://collections.ushmm.org/search/catalog/irn1004727
45. Voinea, D. V. (2025). The algorithmic auteur: AI, cultural production, and the reconfiguration of audiovisual media. Social Sciences and Education Research Review, 12(1), 256–268. https://doi.org/10.5281/zenodo.15804554
46. Wasielewski, A. (2024). Unnatural images: On AI-generated photographs. Critical Inquiry, 51(1), 1–29. https://doi.org/10.1086/731729
47. Wodak, R., & Meyer, M. (2016). Critical discourse studies: History, agenda, theory, and methodology. In R.
48. Wodak & M. Meyer (Eds.), Methods of critical discourse studies (3rd ed., pp. 1–22). Sage. Xu, Z., & Xie, B. (2026). The application of artificial intelligence in film and television script creation. Discover Artificial Intelligence, 6, Article 78. https://doi.org/10.1007/s44163-025-00741-8