Co-Writing Screenplays and Theatre Scripts with Language Models: An Evaluation by Industry Professionals
Authors: Piotr Mirowski, Kory W. Mathewson, Jaylen Pittman, Richard Evans
AI-generated Key Points
- Dramatron is an interactive co-writing tool that uses language models (LLMs) to generate scripts and screenplays
- LLMs lack long-range semantic coherence, so the researchers applied them hierarchically in Dramatron
- Prompt chaining and building structural context were used to generate complete scripts with titles, characters, story beats, location descriptions, and dialogue
- A user study involving 15 theatre and film industry professionals was conducted to evaluate the effectiveness of Dramatron as a co-creative system
- Participants co-wrote scripts with Dramatron and provided critical reflections through open-ended interviews
- Independent reviewers watched stagings of the works to gather feedback
- Results show that Dramatron can be a valuable tool for human-machine co-creativity in writing
- The study raises ethical considerations regarding the use of LLMs for creative purposes such as plagiarism and bias
- This research expands understanding of co-creativity and highlights the potential benefits and challenges of using hierarchical text generation tools like Dramatron in collaborative writing processes.
Abstract: Language models are increasingly attracting interest from writers. However, such models lack long-range semantic coherence, limiting their usefulness for longform creative writing. We address this limitation by applying language models hierarchically, in a system we call Dramatron. By building structural context via prompt chaining, Dramatron can generate coherent scripts and screenplays complete with title, characters, story beats, location descriptions, and dialogue. We illustrate Dramatron's usefulness as an interactive co-creative system with a user study of 15 theatre and film industry professionals. Participants co-wrote theatre scripts and screenplays with Dramatron and engaged in open-ended interviews. We report critical reflections both from our interviewees and from independent reviewers who watched stagings of the works to illustrate how both Dramatron and hierarchical text generation could be useful for human-machine co-creativity. Finally, we discuss the suitability of Dramatron for co-creativity, ethical considerations -- including plagiarism and bias -- and participatory models for the design and deployment of such tools.
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