Creativity in Crisis? A Study of AI’s Disruption of the Creative Production Process in Hollywood
Authors
Central University, Pokuase, Accra (Ghana)
Article Information
DOI: 10.51244/IJRSI.2025.1210000295
Subject Category: Banking and Finance
Volume/Issue: 12/10 | Page No: 3392-3411
Publication Timeline
Submitted: 2025-11-04
Accepted: 2025-11-11
Published: 2025-11-20
Abstract
This study investigates the influence of artificial intelligence (AI) on Hollywood’s creative production processes, with a particular focus on how technological adoption is reshaping roles, workflows, and notions of authorship. Drawing on an interpretivist paradigm and a qualitative research design, the study employed document analysis of industry reports, union statements, scholarly publications, and media sources published between 2018 and 2024.
The findings reveal that AI has been incorporated into multiple stages of filmmaking, including concept development, screenwriting, casting, visual effects, editing, and production planning. While these tools primarily function as supplementary aids that enhance efficiency and expand creative options, concerns persist about reduced human agency, job security, and cultural originality. Stakeholder perceptions vary: producers and executives often emphasize efficiency and cost reduction, whereas writers, performers, and technical staff express unease about the erosion of creative sovereignty and skill development. Labor unions such as the Writers Guild of America (WGA) and SAG-AFTRA have begun to push for contractual safeguards addressing issues of authorship, copyright, and likeness protection.
The study concludes that AI’s integration into Hollywood is negotiated rather than uniform, marked by tensions between innovation and creative integrity. It highlights the need for regulatory frameworks, ethical oversight, and skill development initiatives to ensure that technological progress does not compromise artistic expression, labor conditions, or cultural diversity. By situating these findings within broader theoretical and empirical debates, the research contributes to ongoing discussions on the future of creativity in the age of intelligent machines.
Keywords
Hollywood, Creativity, AI’s Disruption, Creative Production
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References
1. Acemoglu, D., & Restrepo, P. (2019). "Automation and new tasks: How technology displaces and reinstates labor." Journal of Economic Perspectives, 33(2), 3–30. https://doi.org/10.1257/jep.33.2.3. [Google Scholar] [Crossref]
2. Ali, S., Devasia, N., Park, H. W., & Breazeal, C. (2021). Social robots as creativity eliciting agents. Frontiers in Robotics and AI, 8, 673730. https://doi.org/10.3389/frobt.2021.673730. [Google Scholar] [Crossref]
3. American Civil Liberties Union (ACLU). (2022). Position Paper: AI, Copyright, and Freedom of Expression in Media. ACLU. [Google Scholar] [Crossref]
4. Anantrasirichai, N., & Bull, D. (2022). Artificial intelligence in the creative industries: a review. Artificial intelligence review, 55(1), 589-656. https://doi.org/10.1007/s10462-021-10039-7. [Google Scholar] [Crossref]
5. Askar, N. (2024). Entertainers vs AI: A Comparative Analysis of the Unionized and Non-Unionized Entertainers' Approaches to AI. Loy. LA Ent. L. Rev., 45, 91. [Google Scholar] [Crossref]
6. Autor, D. H., & Dorn, D. (2013). "The growth of low-skill service jobs and the polarization of the U.S. labor market." American Economic Review, 103(5), 1553–1597. https://doi.org/10.1257/aer.103.5.1553. [Google Scholar] [Crossref]
7. Azzarelli, A., Anantrasirichai, N., & Bull, D. R. (2025). Intelligent Cinematography: a review of AI research for cinematographic production. Artificial Intelligence Review, 58, 108. https://doi.org/10.1007/s10462-024-11089-3. [Google Scholar] [Crossref]
8. Bărbulescu, A., & Zhen, L. (2024). Forecasting the River Water Discharge by Artificial Intelligence Methods. Water, 16(9), 1248. https://doi.org/10.3390/w16091248. [Google Scholar] [Crossref]
9. Naqvi, S. M., He, R., & Kaur, H. (2025). Catalyst for Creativity or a Hollow Trend?: A Cross-Level Perspective on The Role of Generative AI in Design. Proceedings of CHI 2025. DOI: 10.1145/3706598.3713233. [Google Scholar] [Crossref]
10. Barthes, R. (1967). Le discours de l’histoire. Social Science Information, 6(4), 63–75. https://doi.org/10.1177/053901846700600404. [Google Scholar] [Crossref]
11. Bender, J. (2024). Automation and artistry: Navigating the rise of AI in post-production. Film Production Studies, 12(1), 34–52. https://doi.org/10.1080/21568235.2024.1987412. [Google Scholar] [Crossref]
12. Bender, S. (2024). Generative-AI, the media industries, and the disappearance of human creative labour. Media Practice and Education, 1–18. https://doi.org/10.1080/25741136.2024.2355597. [Google Scholar] [Crossref]
13. Biermann, O. C., Ma, N. F., & Yoon, D. (2022, June). From tool to companion: Storywriters want AI writers to respect their personal values and writing strategies. In Proceedings of the 2022 ACM Designing Interactive Systems Conference (pp. 1209-1227). https://doi.org/10.1145/3532106.3533506. [Google Scholar] [Crossref]
14. Braun, V., & Clarke, V. (2022). Thematic analysis: A practical guide (pp. 1–252). SAGE Publications. https://doi.org/10.4135/9781529781585 [Google Scholar] [Crossref]
15. British Film Institute (BFI). (2022). AI in the UK Film Sector: Risks and Opportunities. BFI Research Report. [Google Scholar] [Crossref]
16. Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. Proceedings of Machine Learning Research, 81, 1–15. https://doi.org/10.48550/arXiv.1801.08921. [Google Scholar] [Crossref]
17. California State Legislature. (2023). California AI Regulation Act (Film and Media Provision). California State Government. [Google Scholar] [Crossref]
18. Cave, S., & Dihal, K. (2020). The whiteness of AI. Philosophy & Technology, 33(4), 685–703. https://doi.org/10.1007/s13347-020-00415-6. [Google Scholar] [Crossref]
19. Chen, R. (2020). “Co-Authorship with Algorithms: The Promise and Limits of AI in Scriptwriting.” New Media & Society, 22(8), 1563–1581. https://doi.org/10.1177/1461444819890402. [Google Scholar] [Crossref]
20. Chen, R. (2020). “Co-Authorship with Algorithms: The Promise and Limits of AI in Scriptwriting.” New Media & Society, 22(8), 1563–1581. https://doi.org/10.1177/1461444819890402. [Google Scholar] [Crossref]
21. Cheyroux, E., & Godet, A. (2022). Introduction: Film Festivals – Close-Up on New Research. Journal of Festive Studies, 4(1), 5–22. https://doi.org/10.33823/jfs.2022.4.1.157. [Google Scholar] [Crossref]
22. Deloitte. (2023). AI in Media & Entertainment: 2023 Industry Trends. Deloitte Insights. [Google Scholar] [Crossref]
23. Directors Guild of America (DGA). (2022). Policy Brief: Artificial Intelligence in Directing and Postproduction. Directors Guild of America. [Google Scholar] [Crossref]
24. Elkins, J. (2023). Generative AI and the future of screenwriting: Opportunities and risks. Journal of Media Innovation, 9(2), 45–61. https://doi.org/10.1080/27696520.2023.1987654. [Google Scholar] [Crossref]
25. Erdem, S. (2025). The synthesis between artificial intelligence and editing stories of the future. In U. Kilinç (Ed.), Transforming Cinema with Artificial Intelligence (pp. 221–240). IGI Global Scientific Publishing. [Google Scholar] [Crossref]
26. https://doi.org/10.4018/979-8-3693-3916-9.ch009. [Google Scholar] [Crossref]
27. European Audiovisual Observatory. (2022). AI and the European Film Industry: Regulatory Perspectives. Strasbourg: European Audiovisual Observatory. [Google Scholar] [Crossref]
28. Fairclough, N. (2013). Critical discourse analysis: The critical study of language (2nd ed.). Routledge. https://doi.org/10.4324/9781315834368. [Google Scholar] [Crossref]
29. Fairclough, N. (2021). Language and power (3rd ed., pp.1–319) Routledge. https://doi.org/10.4324/9780429282652. [Google Scholar] [Crossref]
30. Film Independent. (2022). Case Study: Independent Filmmakers and AI Tools in Production. Film Independent. [Google Scholar] [Crossref]
31. Fisk, C. L. (2023). The Different American Legal Structures for Unionization of Writers for Stage and Screen. In The Palgrave Handbook of Screenwriting Studies (pp. 527-541). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-20769-3_28. [Google Scholar] [Crossref]
32. Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Oxford Martin School Working Paper. Retrieved from https://www.oxfordmartin.ox.ac.uk/downloads/academic/future-of-employment.pdf [Google Scholar] [Crossref]
33. Fukuda‐Parr, S., & Gibbons, E. (2021). Emerging consensus on ‘ethical AI’: Human rights critique of stakeholder guidelines. Global Policy, 12, 32-44. https://doi.org/10.1111/1758-5899.12965. [Google Scholar] [Crossref]
34. George, A. S., Baskar, T., & Pandey, D. (2024). Establishing Global AI Accountability: Training Data Transparency, Copyright, and Misinformation. Partners Universal Innovative Research Publication, 2(3), 75-91. https://doi.org/10.5281/zenodo.11659602. [Google Scholar] [Crossref]
35. Green, B. R. (2023). The Artist’s Code: Technology and the Optimization of Creativity in Hollywood (Doctoral dissertation). University of California, Los Angeles. [Google Scholar] [Crossref]
36. Green, M. (2024). Audience attitudes towards AI-generated media: Trust, transparency, and authenticity. Journal of Media and Society, 16(2), 98–117. https://doi.org/10.1177/20563051241234567. [Google Scholar] [Crossref]
37. Günar, A. (2025). Economic Political and Social Consequences of AI: Understanding the AI Technologies’ Influence with Creative Destruction. In Economic and Political Consequences of AI: Managing Creative Destruction (pp. 1–20). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-70360.ch001. [Google Scholar] [Crossref]
38. Gunar, J. (2025). Artificial intelligence and creative disruption: Revisiting Schumpeter in the digital age. Journal of Innovation Studies, 12(1), 45–63. https://doi.org/10.1080/27688421.2025.000123. [Google Scholar] [Crossref]
39. Hermann, I. (2023). Artificial intelligence in fiction: between narratives and metaphors. AI & Society, 38(1), 319–329. https://doi.org/10.1007/s00146-021-01299-6. [Google Scholar] [Crossref]
40. Hollywood Reporter. (2023). “AI-Generated Films: A New Frontier or Existential Threat?” The Hollywood Reporter. https://www.hollywoodreporter.com/tech/ai-generated-films-2023. [Google Scholar] [Crossref]
41. Hudson, A. D., Finn, E., & Wylie, R. (2023). What can science fiction tell us about the future of artificial intelligence policy? AI & Society, 38(1), 197–211. https://doi.org/10.1007/s00146-021-01273-2. [Google Scholar] [Crossref]
42. Hutson, J. (2024). From Simulacra to Reanimation: Resurrecting the (Un) Dead. In Art and Culture in the Multiverse of Metaverses: Immersion, Presence, and Interactivity in the Digital Age (pp. 173–190). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-66320-8_6. [Google Scholar] [Crossref]
43. International Labour Organization (ILO). (2022). The Future of Work in Creative Industries: Impacts of AI. ILO Research Brief. [Google Scholar] [Crossref]
44. International Labour Organization (ILO). (2022). The Future of Work in Creative Industries: Impacts of AI. ILO Research Brief. [Google Scholar] [Crossref]
45. Jabotinsky, H. Y., & Lavi, M. (2024). Can ChatGPT and the Like Be Your Co-Authors? Cardozo Arts & Entertainment Law Journal, 42, 347. Available at https://papers.ssrn.com/abstract=4528953. [Google Scholar] [Crossref]
46. Jasim, Y. A., & Awqati, A. J. (2025). Distinguishing Human Creativity from AI-Generated Literary Texts. Journal of Prospective Researches, 25(2), 40-47. http://dx.doi.org/10.61704/pr.494. [Google Scholar] [Crossref]
47. Kavitha, L. (2023). Copyright challenges in the artificial intelligence revolution: Transforming the film industry from script to screen. Trinity Law Review, 4(1), 1-8. https://doi.org/10.48165/TLR.2024.4.1.1. [Google Scholar] [Crossref]
48. Kollmann, T., & Kollmann, J. (2025). Artificial entrepreneurship: Generative AI and the future of innovation. Technology Forecasting and Social Change, 204, 123678. https://doi.org/10.1016/j.techfore.2025.123678. [Google Scholar] [Crossref]
49. Kollmann, T., & Kollmann, N. (2025). Digital Innopreneurship 2: The Evaluation of Collaboration between Corporates and Startups in the Digital Economy. Science, 13(2), 135–154. https://doi.org/10.11648/j.sjbm.20251302.18. [Google Scholar] [Crossref]
50. Lawler, J., & Waldner, D. (2023). Interpretivism versus positivism in an age of causal inference. In H. Kincaid & J. Van Bouwel (Eds.), The Oxford Handbook of Philosophy of Political Science (pp. 221–242). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780197519806.013.11. [Google Scholar] [Crossref]
51. Lee, H. K. (2022). Rethinking creativity: Creative industries, AI and everyday creativity. Media, Culture & Society, 44(3), 601–612. https://doi.org/10.1177/01634437221077009. [Google Scholar] [Crossref]
52. Lee, M. (2022). Automation, inequality, and the creative industries: A labour economics perspective. Cultural Trends, 31(4), 343–359. https://doi.org/10.1080/09548963.2022.2103274. [Google Scholar] [Crossref]
53. Lemley, M. A. (2024). How Generative AI Turns Copyright Upside Down. Science & Technology Law Review, 25(2), 21–50. https://doi.org/10.52214/stlr.v25i2.12761. [Google Scholar] [Crossref]
54. Liu, X., & Liu, Z. (2024). A hybrid online and offline teaching effectiveness evaluation method for literary theory courses. Journal of Computational Methods in Sciences and Engineering, 24(6). https://doi.org/10.1177/14727978241299663. [Google Scholar] [Crossref]
55. Liu, Z. (2024). Analysis of the Impact of Artificial Intelligence on the Media and Film Industries. Lecture Notes in Education Psychology and Public Media, 35, 219-223. http://dx.doi.org/10.54254/27537048/35/20232112. [Google Scholar] [Crossref]
56. Lu, H., & Chu, H. (2023). Let the dead talk: How deepfake resurrection narratives influence audience response in prosocial contexts. Computers in Human Behavior, 145, 107761. https://doi.org/10.1016/j.chb.2023.107761. [Google Scholar] [Crossref]
57. Lucchi, N. (2024). ChatGPT: A Case Study on Copyright Challenges for Generative Artificial Intelligence Systems. European Journal of Risk Regulation, 15(3), 602–624. doi:10.1017/err.2023.59. [Google Scholar] [Crossref]
58. Lugrin, C. Pelachaud, & D. Traum (Eds.), the Handbook on Socially Interactive Agents: 20 years of Research on Embodied Conversational Agents, Intelligent Virtual Agents, and Social Robotics, Volume 2: Interactivity, Platforms, Application (pp. 463–492). Association for Computing Machinery. https://doi.org/10.1145/3563659.3563674. [Google Scholar] [Crossref]
59. Mayring, P. (2014). Qualitative content analysis: Theoretical foundation, basic procedures and software solution. Klagenfurt. https://doi.org/10.17169/fqs-15.3.2119. [Google Scholar] [Crossref]
60. McLuhan, M. (1964). Understanding media: The extensions of man. McGraw-Hill. https://doi.org/10.4324/9781315025483. [Google Scholar] [Crossref]
61. McLuhan, M. (1964). Understanding Media: The Extensions of Man. McGraw-Hill. [Google Scholar] [Crossref]
62. Mehrotra, C. (2024). AI: Redefining Creativity and Revolutionizing the Art of Writing. International Journal of Innovations in Science, Engineering and Management, 3(Special Issue 2), 129–133. https://doi.org/10.69968/ijisem.2024v3si2129-133. [Google Scholar] [Crossref]
63. Meydan, C. H., & Akkaş, H. (2024). The role of triangulation in qualitative research: Converging perspectives. In A. Elhami, A. Roshan, & H. Chandan (Eds.), Principles of conducting qualitative research in multicultural settings (pp. 98–129). IGI Global. https://doi.org/10.4018/979-8-3693-3306-8.ch006. [Google Scholar] [Crossref]
64. Miller, A. (2022). “Machine Creativity or Creative Tools? AI in Hollywood’s Post-Production.” Journal of Cultural Production, 17(3), 212–230. https://doi.org/10.1080/17530350.2022.1992387. [Google Scholar] [Crossref]
65. MIT Media Lab. (2022). Showcase on Human–AI Collaborative Storytelling. MIT Media Lab. [Google Scholar] [Crossref]
66. Motion Picture Association (MPA). (2023). AI and Intellectual Property Rights in Hollywood. MPA White Paper. [Google Scholar] [Crossref]
67. Murdoch, B. (2021). Privacy and artificial intelligence: challenges for protecting health information in a new era. BMC medical ethics, 22, 1-5. https://doi.org/10.1186/s12910-021-00687-3. [Google Scholar] [Crossref]
68. Netflix. (2023). Annual Report: Experimentation with AI in Storyboarding and Postproduction. Netflix Media Center. [Google Scholar] [Crossref]
69. New York Times. (2023). “Actors Protest AI Use in Hollywood Contracts.” The New York Times. https://www.nytimes.com/2023/07/ai-actors-hollywood [Google Scholar] [Crossref]
70. Nissim, G., & Simon, T. (2021). The future of labor unions in the age of automation and at the dawn of AI. Technology in Society, 67, 101732. https://doi.org/10.1016/j.techsoc.2021.101732. [Google Scholar] [Crossref]
71. Okun, J. A., & Zwerman, S. (2020). The VES Handbook of Visual Effects: Industry Standard VFX Practices and Procedures. Routledge. https://doi.org/10.4324/9780429455934. [Google Scholar] [Crossref]
72. Perez, C. (2002). Technological revolutions and financial capital: The dynamics of bubbles and golden ages. Edward Elgar Publishing. [Google Scholar] [Crossref]
73. Pervin, N., & Mokhtar, M. (2022). The interpretivist research paradigm: A subjective notion of a social context. International Journal of Academic Research in Progressive Education and Development, 11(2), 419–428. https://doi.org/10.6007/IJARPED/v11-i2/12938. [Google Scholar] [Crossref]
74. Postman, N. (1970). The reformed English curriculum. In A. C. Eurich (Ed.), High school 1980: The shape of the future in American secondary education (pp. 160–168). Pitman. https://doi.org/10.4324/9781315005813. [Google Scholar] [Crossref]
75. Pretorius, L. (2024). Demystifying research paradigms: Navigating ontology, epistemology, and axiology in research. The Qualitative Report, 29(10), 2698–2715. DOI: 10.46743/2160-3715/2024.7632. [Google Scholar] [Crossref]
76. PwC. (2022). Global Entertainment and Media Outlook 2022–2026. PricewaterhouseCoopers. https://www.pwc.com/outlook2022. [Google Scholar] [Crossref]
77. Re-evaluating creative labor in the age of artificial intelligence: A qualitative case study of creative workers’ perspectives on technological transformation in creative industries (2025). AI & Society, 40, 4119-4130. https://doi.org/10.1007/s00146-025-02180-6. [Google Scholar] [Crossref]
78. Rodriguez, L. (2023). “Personalized streaming and interactive narratives: The role of AI in audience engagement.” Media, Culture & Society, 45(4), 567–584. https://doi.org/10.1177/01634437221123456. [Google Scholar] [Crossref]
79. Ruotsalainen, J., & Heinonen, S. (2015). Media ecology and the future ecosystemic society. Futures, 73, 80–92. https://doi.org/10.1016/j.futures.2015.07.007. [Google Scholar] [Crossref]
80. SAG-AFTRA. (2023). Statement on AI and Digital Replication of Performers. Retrieved from SAGAFTRA. [Google Scholar] [Crossref]
81. SAG-AFTRA. (2024). AI and performers’ rights: Policy guidelines. SAG-AFTRA. https://doi.org/10.5281/zenodo.10562453. [Google Scholar] [Crossref]
82. Schumpeter, J. A. (1942). Capitalism, socialism and democracy. Harper & Brothers. https://doi.org/10.4324/9781315135564. [Google Scholar] [Crossref]
83. Schwandt, T. A. (1994). Constructivist, interpretivist approaches to human inquiry. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of qualitative research (pp. 118–137). Thousand Oaks, CA: Sage. [Google Scholar] [Crossref]
84. Schwandt, T. A. (2014). The Sage dictionary of qualitative inquiry (4th ed.). Sage. https://doi.org/10.4135/9781483398969. [Google Scholar] [Crossref]
85. Screen Actors Guild – American Federation of Television and Radio Artists (SAG-AFTRA). (2023). Statement on AI and Digital Replication of Performers. SAG-AFTRA. https://www.sagaftra.org/files/AI_Statement_2023.pdf. [Google Scholar] [Crossref]
86. Shamanth, N., Sagar, T. R., & Priyanga, P. (2024, November). The Intersection of Art and AI: Innovations in Creative Collaboration. In 2024 International Conference on IoT, Communication and Automation Technology (ICICAT) (pp. 874–879). IEEE. https://doi.org/10.1109/ICICAT62666.2024.10923276. [Google Scholar] [Crossref]
87. Siala, H., & Wang, Y. (2022). SHIFTing artificial intelligence to be responsible in healthcare: A systematic review. Social Science & Medicine, 296, 114782. https://doi.org/10.1016/j.socscimed.2022.114782. [Google Scholar] [Crossref]
88. Smith, J. (2021). “Algorithms at the Writers’ Table: AI and the Changing Nature of Screen Authorship.” Journal of Media Studies, 34(2), 145–168. https://doi.org/10.1080/02614340.2021.1875602. [Google Scholar] [Crossref]
89. Smith, J. A., Flowers, P., & Larkin, M. (2022). Interpretative phenomenological analysis: Theory, method and research (2nd ed., pp. 1–264). SAGE Publications. https://doi.org/10.4135/9781529714385 [Google Scholar] [Crossref]
90. Sommer, E. (2024). Real Concerns for an Artificial Threat: Artists, AI, and the Battle to Script Hollywood's Future. Nev. LJ, 25, 449. https://scholars.law.unlv.edu/nlj/vol25/iss2/7. [Google Scholar] [Crossref]
91. Strate, L. (2017). Media Ecology: An Approach to Understanding the Human Condition. Peter Lang Publishing. https://doi.org/10.3726/978-1-4331-4005-1. [Google Scholar] [Crossref]
92. Sun, P. (2024). A study of artificial intelligence in the production of film. In SHS Web of Conferences, 2024 International Conference on Performing Arts, Human Development and Digitalization (Vol. 185, p. 03004). https://doi.org/10.1051/shsconf/202418303004. [Google Scholar] [Crossref]
93. Sun, P., & Zuo, X. (2024). Evolution and history of research philosophy. Journal of Management Research, 24(1), 28–61. https://doi.org/10.5281/zenodo.13862367. [Google Scholar] [Crossref]
94. Tang, X. (2025). Intellectual property law as labor policy. NYUL Rev., 100, 62. [Google Scholar] [Crossref]
95. Tang, Y., Li, H., Lan, M., Ma, X., & Qu, H. (2025). Understanding Screenwriters' Practices, Attitudes, and Future Expectations in Human-AI Co-Creation. arXiv preprint arXiv:2502.16153. https://doi.org/10.48550/arXiv.2502.16153. [Google Scholar] [Crossref]
96. TechCrunch. (2022). “Startups Betting on AI Screenwriting Tools.” TechCrunch. https://techcrunch.com/2022/11/ai-screenwriting-startups. [Google Scholar] [Crossref]
97. Thanh, N. C., & Thanh, T. T. L. (2015). The interconnection between interpretivist paradigm and qualitative methods in education. American Journal of Educational Science, 1(2), 24–27. Retrieved from https://files.eric.ed.gov/fulltext/ED595989. [Google Scholar] [Crossref]
98. Townsend, D. M., & Hunt, R. A. (2019). Entrepreneurial action, creativity, & judgment in the age of artificial intelligence. Journal of Business Venturing Insights, 11, e00126. https://doi.org/10.1016/j.jbvi.2019.e00126. [Google Scholar] [Crossref]
99. Towse, R. (2020). A Textbook of Cultural Economics (3rd ed.). Cambridge University Press. https://doi.org/10.1017/9781108627377. [Google Scholar] [Crossref]
100. Trangbæk, A., & Cecchini, M. (2023). Using the interpretivist methodology. In R. Shaw & C. Eichbaum (Eds.), Handbook on Ministerial and Political Advisers (pp. 123–136). Edward Elgar Publishing. https://doi.org/10.4337/9781800886582. [Google Scholar] [Crossref]
101. UNESCO. (2022). AI and Cultural Diversity in Global Media. UNESCO Report. [Google Scholar] [Crossref]
102. United Nations Educational, Scientific and Cultural Organization (UNESCO). (2022). AI and Cultural Diversity in Global Media. UNESCO Report. [Google Scholar] [Crossref]
103. Variety. (2022). “How AI Is Changing Casting in Hollywood.” Retrieved from [https://variety.com/2022/film/news/ai-casting-hollywood] Variety. [Google Scholar] [Crossref]
104. Variety. (2022). “How AI is Changing Casting in Hollywood.” Variety Magazine. https://variety.com/2022/film/news/ai-casting-hollywood. [Google Scholar] [Crossref]
105. Vaughan, H. (2021). A Green Intervention in Media Production Culture Studies: Environmental Values, Political Economy and Mobile Production. Environmental Values, 30(2), 193–214. https://doi.org/10.3197/096327120X15752810324057. [Google Scholar] [Crossref]
106. Verdecchia, R., Sallou, J., & Cruz, L. (2023). A systematic review of Green AI. WIREs Data Mining and Knowledge Discovery, 13(4), e1507. https://doi.org/10.1002/widm.1507. [Google Scholar] [Crossref]
107. Vincent, J. (2023). Hollywood’s uneasy embrace of artificial intelligence. Film Quarterly, 77(1), 14–23. https://doi.org/10.1525/fq.2023.77.1.14. [Google Scholar] [Crossref]
108. Vincent, J. (2023, May 8). Hollywood’s use of AI in casting raises ethical concerns. The Verge. https://doi.org/10.5281/zenodo.7987453. [Google Scholar] [Crossref]
109. WGA. (2023). Artificial intelligence and authorship policy statement. Writers Guild of America. https://doi.org/10.5281/zenodo.10437652. [Google Scholar] [Crossref]
110. Wong, L. P. W. (2024). Artificial intelligence and job automation: Challenges for secondary students’ career development and life planning. Merits, 4(4), 370–399. https://doi.org/10.3390/merits4040027. [Google Scholar] [Crossref]
111. World Economic Forum (WEF). (2023). AI and the Future of the Creative Economy. WEF White Paper. 111. Writers Guild Foundation Archive. (2021). Survey on Writers’ Perceptions of AI in Screenwriting. Writers Guild Foundation. [Google Scholar] [Crossref]
112. Writers Guild of America (WGA). (2023). WGA Negotiation Report on AI Use in Screenwriting. Writers Guild of America. https://www.wga.org/uploadedfiles/members/memberinfo/contracts/WGA_AI_Report_202.Pdf. [Google Scholar] [Crossref]
113. Writers Guild of America. (2023, May 1). Summary of the 2023 WGA Minimum Basic Agreement (MBA). Writers Guild of America. Retrieved from Writers Guild website. [Google Scholar] [Crossref]
114. Xu, W. (2023). AI in HCI Design and User Experience. In AI in HCI Design and User Experience. ArXiv. https://doi.org/10.48550/arXiv.2301.00987. [Google Scholar] [Crossref]
115. Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed., pp. 1–352). SAGE Publications. [Google Scholar] [Crossref]
116. Young, Z. T. (2024). Generative Artificial Intelligence in Hollywood: The Turbulent Future that Lies Ahead. W. Va. L. Rev., 127, 541. [Google Scholar] [Crossref]
117. Zhang, R., Yu, B., Min, J., Xin, Y., Wei, Z., Shi, J. N., … Rao, A. (2025). Generative AI for film creation: A survey of recent advances. arXiv preprint arXiv:2504.08296. https://doi.org/10.48550/arXiv.2504.08296. [Google Scholar] [Crossref]
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