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Social Dynamics of AI Support in Creative Writing
Open accessAbstract
Recently, large language models have made huge advances in generating coherent, creative text. While much research focuses on how users can interact with language models, less work considers the social-technical gap that this technology poses. What are the social nuances that underlie receiving support from a generative AI? In this work we ask when and why a creative writer might turn to a computer versus a peer or mentor for support. We interview 20 creative writers about their writing practice and their attitudes towards both human and computer support. We discover three elements that govern a writer’s interaction with support actors: 1) what writers desire help with, 2) how writers perceive potential support actors, and 3) the values writers hold. We align our results with existing frameworks of writing cognition and creativity support, uncovering the social dynamics which modulate user responses to generative technologies.
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“Yet, only a handful of user studies have investigated how professional writers perceive and use AI systems [13,27,28]”
From Playwriting with Large Language Models: Perceived Features, Interaction Strategies and Outcomes (2024) · cites this paper as [27]
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“Empirical studies describing how users evaluate LLMs are still a minority and difficult to generalise due to a variation of participants, methods, systems, and disciplinary perspectives [13,27,28,38,47].”
From Playwriting with Large Language Models: Perceived Features, Interaction Strategies and Outcomes (2024) · cites this paper as [27]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Current systems fail to satisfy the writers' needs because they do not understand their intentions [27].”
From Playwriting with Large Language Models: Perceived Features, Interaction Strategies and Outcomes (2024) · cites this paper as [27]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The models are often described as biased.They perpetuate stereotypes and jeopardise trust in the generated content [27,38].”
From Playwriting with Large Language Models: Perceived Features, Interaction Strategies and Outcomes (2024) · cites this paper as [27]
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“Despite these limitations, playwrights identified utility at different stages of creative writing, from brainstorming through the summarisation of relevant sources to editing [27,42,47].”
From Playwriting with Large Language Models: Perceived Features, Interaction Strategies and Outcomes (2024) · cites this paper as [27]
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“From writers' perspectives, authenticity often determines the value of their work, which co-writing with AI might potentially threaten [18].”
From 'It was 80% me, 20% AI': Seeking Authenticity in Co-Writing with Large Language Models (2025) · cites this paper as [18]
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“To support broader adoption of AI co-writing systems among writers, it is crucial to consider perceived agency and perceived ownership, as these factors can influence a writer's long-term satisfaction with such systems [23].”
From Where Do I 'Add the Egg'?: Exploring Agency and Ownership in AI Creative Co-Writing Systems (2026) · cites this paper as [23]
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“However, these accounts focus on isolated stages of use and therefore provide only snapshots of human-AI collaboration.”
From How Do Human Creators Embrace Human-AI Co-Creation? A Perspective on Human Agency of Screenwriters (2026) · cites this paper as [19]
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“As a result, it faces similar challenges to creative writing, such as a lack of inspiration and guidance [34].”
From Understanding Screenwriters' Practices, Attitudes, and Future Expectations in Human-AI Co-Creation (2025) · cites this paper as [34]
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“Not only did the participants report utility for editorial tasks [27,42,47], but they also acknowledge potential for idea generation [13,38,42].”
From Playwriting with Large Language Models: Perceived Features, Interaction Strategies and Outcomes (2024) · cites this paper as [27]
The cited source says what the claim attributes to it.
In the citing paper
“They provide non-judgemental support to human creativity [27], which comes at no cost to their users.”
From Playwriting with Large Language Models: Perceived Features, Interaction Strategies and Outcomes (2024) · cites this paper as [27]
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“A final barrier was identified in the politics embedded in LLMs.”
From Playwriting with Large Language Models: Perceived Features, Interaction Strategies and Outcomes (2024) · cites this paper as [27]
The cited source says what the claim attributes to it.
In the citing paper
“From writers' perspectives, authenticity often determines the value of their work, which co-writing with AI might potentially threaten [18].”
From 'It was 80% me, 20% AI': Seeking Authenticity in Co-Writing with Large Language Models (2025) · cites this paper as [18]
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“Users may have preconceived notions about AI systems, so metaphors can help users understand the capabilities of an AI agent by proposing an alternative mental model [11, 23].”
From Where Do I 'Add the Egg'?: Exploring Agency and Ownership in AI Creative Co-Writing Systems (2026) · cites this paper as [23]
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Metadata
- Authors
- Gero, K. I., Long, T., & Chilton, L. B.
- Affiliations
- Columbia University (US)
- Venue
- Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2023-04-19
- Pages
- 1-15
- OpenAlex
- W4366594764
- Cited by
- 129
- References
- 24
- Citations by year
- 2026: 43 · 2025: 41 · 2024: 42 · 2023: 3
- FWCI
- 29.94
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Funders
- National Science Foundation (2129020)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art, Technology, and Culture
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Keywords
- generative AI, creative writing, large language models, peer support, mentor support, writing cognition, creativity support
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