mlsanityData to 14 Oct 2026

"It was 80% me, 20% AI": Seeking Authenticity in Co-Writing with Large Language Models

arXiv 2411.13032 ↗First posted 20 Nov 2024cs.HC cs.AI cs.CYcited by 14

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Abstract (arXiv)

Given the rising proliferation and diversity of AI writing assistance tools, especially those powered by large language models (LLMs), both writers and readers may have concerns about the impact of these tools on the authenticity of writing work. We examine whether and how writers want to preserve their authentic voice when co-writing with AI tools and whether personalization of AI writing support could help achieve this goal. We conducted semi-structured interviews with 19 professional writers, during which they co-wrote with both personalized and non-personalized AI writing-support tools. We supplemented writers' perspectives with opinions from 30 avid readers about the written work co-produced with AI collected through an online survey. Our findings illuminate conceptions of authenticity in human-AI co-creation, which focus more on the process and experience of constructing creators' authentic selves. While writers reacted positively to personalized AI writing tools, they believed the form of personalization needs to target writers' growth and go beyond the phase of text production. Overall, readers' responses showed less concern about human-AI co-writing. Readers could not distinguish AI-assisted work, personalized or not, from writers' solo-written work and showed positive attitudes toward writers experimenting with new technology for creative writing.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 17 of its 66 references that are in the map. First posted on arXiv 20 Nov 2024.

Builds on

17 of 66 references.

References · 17

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2022News Summarization and Evaluation in the Era of GPT-3cited by 327
  3. 2022CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilitiescited by 249
  4. 2022Co-Writing Screenplays and Theatre Scripts with Language Models: An Evaluation by Industry Professionalscited by 191
  5. 2023Co-Writing with Opinionated Language Models Affects Users' Viewscited by 148
  6. 2021A Recipe For Arbitrary Text Style Transfer with Large Language Modelscited by 107
  7. 2022Human heuristics for AI-generated language are flawedcited by 105
  8. 2021Sparks: Inspiration for Science Writing using Language Modelscited by 80
  9. 2022Creative Writing with an AI-Powered Writing Assistant: Perspectives from Professional Writerscited by 69
  10. 2021The Impact of Multiple Parallel Phrase Suggestions on Email Input and Composition Behaviour of Native and Non-Native English Writerscited by 61
  11. 2022Beyond Text Generation: Supporting Writers with Continuous Automatic Text Summariescited by 47
  12. 2023VISAR: A Human-AI Argumentative Writing Assistant with Visual Programming and Rapid Draft Prototypingcited by 46
5 more
  1. 2020PANDORA Talks: Personality and Demographics on Redditcited by 40
  2. 2023Choice Over Control: How Users Write with Large Language Models using Diegetic and Non-Diegetic Promptingcited by 36
  3. 2023Designing Participatory AI: Creative Professionals' Worries and Expectations about Generative AIcited by 20
  4. 2023Storyfier: Exploring Vocabulary Learning Support with Text Generation Modelscited by 12
  5. 2024Scaling Laws for Economic Productivity: Experimental Evidence in LLM-Assisted Translationcited by 5

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Citing papers per year: 2025: 5; 2026: 9.

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