# How Does the Disclosure of AI Assistance Affect the Perceptions of Writing?

arXiv: https://arxiv.org/abs/2410.04545 · HTML: https://mlsanity.com/paper/2410.04545/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 36 references that are in the map.
- First posted on arXiv 6 Oct 2024.

## Builds on (most cited first, 15 of 15)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [All That's 'Human' Is Not Gold: Evaluating Human Evaluation of Generated Text](https://mlsanity.com/paper/2107.00061/) (2021)
- [Automatic Detection of Generated Text is Easiest when Humans are Fooled](https://mlsanity.com/paper/1911.00650/) (2019)
- [CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities](https://mlsanity.com/paper/2201.06796/) (2022)
- [PersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traits](https://mlsanity.com/paper/2305.02547/) (2023)
- [Co-Writing Screenplays and Theatre Scripts with Language Models: An Evaluation by Industry Professionals](https://mlsanity.com/paper/2209.14958/) (2022)
- [Co-Writing with Opinionated Language Models Affects Users' Views](https://mlsanity.com/paper/2302.00560/) (2023)
- [Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text](https://mlsanity.com/paper/2107.01294/) (2021)
- [A Design Space for Intelligent and Interactive Writing Assistants](https://mlsanity.com/paper/2403.14117/) (2024)
- [The Impact of Multiple Parallel Phrase Suggestions on Email Input and Composition Behaviour of Native and Non-Native English Writers](https://mlsanity.com/paper/2101.09157/) (2021)
- [VISAR: A Human-AI Argumentative Writing Assistant with Visual Programming and Rapid Draft Prototyping](https://mlsanity.com/paper/2304.07810/) (2023)
- [The Value, Benefits, and Concerns of Generative AI-Powered Assistance in Writing](https://mlsanity.com/paper/2403.12004/) (2024)
- [Choice Over Control: How Users Write with Large Language Models using Diegetic and Non-Diegetic Prompting](https://mlsanity.com/paper/2303.03199/) (2023)
- [LLMs as Writing Assistants: Exploring Perspectives on Sense of Ownership and Reasoning](https://mlsanity.com/paper/2404.00027/) (2024)
- [Comparing Sentence-Level Suggestions to Message-Level Suggestions in AI-Mediated Communication](https://mlsanity.com/paper/2302.13382/) (2023)

## Built on by (most cited first, 12 of 12)

- [From Text to Trust: Empowering AI-assisted Decision Making with Adaptive LLM-powered Analysis](https://mlsanity.com/paper/2502.11919/) (2025)
- [Can Good Writing Be Generative? Expert-Level AI Writing Emerges through Fine-Tuning on High-Quality Books](https://mlsanity.com/paper/2601.18353/) (2026)
- [Readers Prefer Outputs of AI Trained on Copyrighted Books over Expert Human Writers](https://mlsanity.com/paper/2510.13939/) (2025)
- [A Multi-Task Evaluation of LLMs' Processing of Academic Text Input](https://mlsanity.com/paper/2508.11779/) (2025)
- ["If You're Very Clever, No One Knows You've Used It": The Social Dynamics of Developing Generative AI Literacy in the Workplace](https://mlsanity.com/paper/2602.01386/) (2026)
- [Accepted with Minor Revisions: Value of AI-Assisted Scientific Writing](https://mlsanity.com/paper/2511.12529/) (2025)
- [From Use to Oversight: How Mental Models Influence User Behavior and Output in AI Writing Assistants](https://mlsanity.com/paper/2604.05166/) (2026)
- [Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs](https://mlsanity.com/paper/2605.29928/) (2026)
- [Effects of Varying LLM Access on Essay Writing Behavior](https://mlsanity.com/paper/2606.00250/) (2026)
- [LLM or Human? Perceptions of Trust and Information Quality in Research Summaries](https://mlsanity.com/paper/2601.15556/) (2026)
- [Human-AI Interaction Traces as Blackout Poetry: Reframing AI-Supported Writing as Found-Text Creativity](https://mlsanity.com/paper/2604.09605/) (2026)
- [AI-Generated Slides: Are They Good? Can Students Tell?](https://mlsanity.com/paper/2605.13532/) (2026)

## Abstract (arXiv)

Recent advances in generative AI technologies like large language models have boosted the incorporation of AI assistance in writing workflows, leading to the rise of a new paradigm of human-AI co-creation in writing. To understand how people perceive writings that are produced under this paradigm, in this paper, we conduct an experimental study to understand whether and how the disclosure of the level and type of AI assistance in the writing process would affect people's perceptions of the writing on various aspects, including their evaluation on the quality of the writing and their ranking of different writings. Our results suggest that disclosing the AI assistance in the writing process, especially if AI has provided assistance in generating new content, decreases the average quality ratings for both argumentative essays and creative stories. This decrease in the average quality ratings often comes with an increased level of variations in different individuals' quality evaluations of the same writing. Indeed, factors such as an individual's writing confidence and familiarity with AI writing assistants are shown to moderate the impact of AI assistance disclosure on their writing quality evaluations. We also find that disclosing the use of AI assistance may significantly reduce the proportion of writings produced with AI's content generation assistance among the top-ranked writings.