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Towards Full Authorship with AI: Supporting Revision with AI-Generated Views (2403.01055v1)

Published 2 Mar 2024 in cs.HC, cs.AI, and cs.CY

Abstract: LLMs are shaping a new user interface (UI) paradigm in writing tools by enabling users to generate text through prompts. This paradigm shifts some creative control from the user to the system, thereby diminishing the user's authorship and autonomy in the writing process. To restore autonomy, we introduce Textfocals, a UI prototype designed to investigate a human-centered approach that emphasizes the user's role in writing. Textfocals supports the writing process by providing LLM-generated summaries, questions, and advice (i.e., LLM views) in a sidebar of a text editor, encouraging reflection and self-driven revision in writing without direct text generation. Textfocals' UI affordances, including contextually adaptive views and scaffolding for prompt selection and customization, offer a novel way to interact with LLMs where users maintain full authorship of their writing. A formative user study with Textfocals showed promising evidence that this approach might help users develop underdeveloped ideas, cater to the rhetorical audience, and clarify their writing. However, the study also showed interaction design challenges related to document navigation and scoping, prompt engineering, and context management. Our work highlights the breadth of the design space of writing support interfaces powered by generative AI that maintain authorship integrity.

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References (5)
  1. Sentiment Bias in Predictive Text Recommendations Results in Biased Writing, in: Graphics Interface 2018, Toronto, Ontario, Canada, 2018, pp. 8–11.
  2. Co-Writing with Opinionated Language Models Affects Users’ Views, in: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023, pp. 1–15. doi:10.1145/3544548.3581196. arXiv:2302.00560.
  3. J. Fitzgerald, Research on Revision in Writing, Review of Educational Research 57 (1987) 481–506. doi:10.2307/1170433. arXiv:1170433.
  4. M. M. Nelson, C. D. Schunn, The Nature of Feedback: How Different Types of Peer Feedback Affect Writing Performance, Instructional Science 37 (2009) 375–401. arXiv:23372520.
  5. J. R. Hayes, What Triggers Revision?, in: G. Rijlaarsdam, L. Allal, L. Chanquoy, P. Largy (Eds.), Revision Cognitive and Instructional Processes, volume 13, Springer Netherlands, Dordrecht, 2004, pp. 9–20. doi:10.1007/978-94-007-1048-1_2.
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