AI Rivalry as a Craft: How Resisting and Embracing Generative AI Reshape Writing Professions
arXiv:2503.09901 · doi:10.1145/3706598.3714035
Abstract
Generative AI (GAI) technologies are disrupting professional writing, challenging traditional practices. Recent studies explore GAI adoption experiences of creative practitioners, but we know little about how these experiences evolve into established practices and how GAI resistance alters these practices. To address this gap, we conducted 25 semi-structured interviews with writing professionals who adopted and/or resisted GAI. Using the theoretical lens of Job Crafting, we identify four strategies professionals employ to reshape their roles. Writing professionals employed GAI resisting strategies to maximize human potential, reinforce professional identity, carve out a professional niche, and preserve credibility within their networks. In contrast, GAI-enabled strategies allowed writers who embraced GAI to enhance desirable workflows, minimize mundane tasks, and engage in new AI-managerial labor. These strategies amplified their collaborations with GAI while reducing their reliance on other people. We conclude by discussing implications of GAI practices on writers' identity and practices as well as crafting theory.
References in corpus (14)
- Art and the science of generative AI: A deeper dive
- GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models
- Expanding Explainability: Towards Social Transparency in AI systems
- CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities
- Large-scale Text-to-Image Generation Models for Visual Artists' Creative Works
- The AI Ghostwriter Effect: When Users Do Not Perceive Ownership of AI-Generated Text But Self-Declare as Authors
- How Knowledge Workers Think Generative AI Will (Not) Transform Their Industries
- "An Adapt-or-Die Type of Situation": Perception, Adoption, and Use of Text-To-Image-Generation AI by Game Industry Professionals
- Writer-Defined AI Personas for On-Demand Feedback Generation
- ABScribe: Rapid Exploration & Organization of Multiple Writing Variations in Human-AI Co-Writing Tasks using Large Language Models
- CatAlyst: Domain-Extensible Intervention for Preventing Task Procrastination Using Large Generative Models
- Ai.llude: Encouraging Rewriting AI-Generated Text to Support Creative Expression
- Authors' Values and Attitudes Towards AI-bridged Scalable Personalization of Creative Language Arts
- When happy accidents spark creativity: Bringing collaborative speculation to life with generative AI