Redefining roles: human–AI collaboration in screenwriting

Spencer, A ORCID: 0000-0002-6786-4706 (2025) 'Redefining roles: human–AI collaboration in screenwriting.' Journal of Screenwriting, 16 (3). pp. 273-286.

Abstract

The use of generative artificial intelligence (AI) is transforming the way we tell stories – from the way we develop ideas to writing and production processes. This article presents a case study that followed the screenwriting processes, supported by generative AI, used in the making of RENO , a short science fiction film, produced by multi-award-winning Bristol-based visual effects (VFX) studio Lux Aeterna. RENO was developed as an industry case study as part of the UKRI-funded MyWorld programme, which explores the future of creative technology innovation in the south-west of the United Kingdom by pioneering new ideas, products and processes. This article shares findings from this case study, achieved through tracking the development of the screenwriting processes developed in the production of RENO , which included a series of interviews with those involved in the process. The findings highlight a nuanced relationship with generative AI, which, while initially embraced as a creative driver, the team ultimately found more valuable in specific creation and production contexts. This case study offers valuable insights for screenwriters, emphasizing the importance of both maintaining human creative control while also experimenting with emerging technologies through a reflective process. The article argues that defining generative AI’s specific role in the screenwriting process, whether in the role of research assistant, character development tool, co-writer/writing partner or editor/critical friend, becomes a crucial part of the creative process.

Item Type:	Article
Keywords:	artificial intelligence, authorship, character development, generative AI, RENO, storytelling, studio Lux Aeterna
Divisions:	Chancelry and Research Management School of Writing, Publishing and the Humanities
Date Deposited:	24 Feb 2026 13:53
Last Modified:	24 Feb 2026 13:53
ISSN:	1759-7137
URN:	https://researchspace.bathspa.ac.uk/id/eprint/17594

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