"It was 80% me, 20% AI": Seeking Authenticity in Co-Writing with Large Language Models
Angel Hsing-Chi Hwang, Q. Vera Liao, Su Lin Blodgett, Alexandra, Olteanu, Adam Trischler

TL;DR
This study explores how professional writers and readers perceive authenticity in co-writing with AI, highlighting the importance of personalization and the generally positive reception of AI-assisted creative writing.
Contribution
It provides empirical insights into authenticity perceptions in human-AI co-creation and evaluates the impact of personalized AI tools on writers' and readers' attitudes.
Findings
Writers value authenticity as a process and experience.
Personalized AI tools are positively received but should support growth.
Readers are less concerned and cannot distinguish AI-assisted work from human-written work.
Abstract
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'…
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Taxonomy
TopicsTopic Modeling
MethodsFocus
