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Teaming Up with an AI: Exploring Human–AI Collaboration in a Writing Scenario with ChatGPT.

Authors :
Luther, Teresa
Kimmerle, Joachim
Cress, Ulrike
Source :
AI. Sep2024, Vol. 5 Issue 3, p1357-1376. 20p.
Publication Year :
2024

Abstract

Recent advancements in artificial intelligence (AI) technologies, particularly in generative pre-trained transformer large language models, have significantly enhanced the capabilities of text-generative AI tools—a development that opens new avenues for human–AI collaboration across various domains. However, the dynamics of human interaction with AI-based chatbots, such as ChatGPT, remain largely unexplored. We observed and analyzed how people interact with ChatGPT in a collaborative writing setting to address this research gap. A total of 135 participants took part in this exploratory lab study, which consisted of engaging with ChatGPT to compose a text discussing the prohibition of alcohol in public in relation to a given statement on risky alcohol consumption. During the writing task, all screen activity was logged. In addition to the writing task, further insights on user behavior and experience were gained by applying questionnaires and conducting an additional short interview with a randomly selected subset of 18 participants. Our results reveal high satisfaction with ChatGPT regarding quality aspects, mainly cognitive rather than affect-based trust in ChatGPT's responses, and higher ratings on perceived competence than on warmth. Compared to other types of prompts, mostly content-related prompts for data, facts, and information were sent to ChatGPT. Mixed-method analysis showed that affinity for technology integration and current use of ChatGPT were positively associated with the frequency of complete text requests. Moreover, prompts for complete texts were associated with more copy–paste behavior. These first insights into co-writing with ChatGPT can inform future research on how successful human–AI collaborative writing can be designed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
26732688
Volume :
5
Issue :
3
Database :
Academic Search Index
Journal :
AI
Publication Type :
Academic Journal
Accession number :
180019735
Full Text :
https://doi.org/10.3390/ai5030065