GhostWriter: Augmenting Collaborative Human-AI Writing Experiences Through Personalization and Agency
Writing is a well-established practice to support ideation and creativity. While Large Language Models (LLMs) have become ubiquitous in providing different kinds of writing assistance to different writers, LLM-powered writing systems often fall short in capturing the nuanced personalization and control necessary for effective support and creative exploration. To address these challenges, we introduce GhostWriter, an AI-enhanced writing design probe that enables users to exercise enhanced agency and personalization. GhostWriter leverages LLMs to implicitly learn the user's intended writing style for seamless personalization, while exposing explicit teaching moments for style refinement and reflection. We study 18 participants who use GhostWriter for editing and creative tasks, observing that it helps users craft personalized text and empowers them by providing multiple ways to steer system output. Based on this study, we present insights on people's relationships with AI-assisted writing and offer design recommendations to promote user agency in similar co-creative systems.
Code (0)
등록된 구현이 없습니다.
Tasks
Prompt EngineeringSimilar Papers 제목 키워드 기반
The AI Ghostwriter Effect: When Users Do Not Perceive Ownership of AI-Generated Text But Self-Declare as Authors
Human-AI interaction in text production increases complexity in authorship. In two empirical studies (n1 = 30 & n2 = 96), we investigate authorship and ownership in human-AI collaboration for personalized language genera…
AttributeText GenerationDetecting Ghostwriters in High Schools
Students hiring ghostwriters to write their assignments is an increasing problem in educational institutions all over the world, with companies selling these services as a product. In this work, we develop automatic tech…
Vocal Bursts Intensity PredictionDeepPavlov at SemEval-2024 Task 8: Leveraging Transfer Learning for Detecting Boundaries of Machine-Generated Texts
The Multigenerator, Multidomain, and Multilingual Black-Box Machine-Generated Text Detection shared task in the SemEval-2024 competition aims to tackle the problem of misusing collaborative human-AI writing. Although the…
Boundary DetectionText DetectionTransfer LearningAugmenting the Author: Exploring the Potential of AI Collaboration in Academic Writing
This workshop paper presents a critical examination of the integration of Generative AI (Gen AI) into the academic writing process, focusing on the use of AI as a collaborative tool. It contrasts the performance and inte…
Inspiration through Observation: Demonstrating the Influence of Automatically Generated Text on Creative Writing
Getting machines to generate text perceived as creative is a long-pursued goal. A growing body of research directs this goal towards augmenting the creative writing abilities of human authors. In this paper, we pursue th…
Language ModellingSentenceText Generation