Design and Evaluation of AI-Aided Writing: Managing User Burden and Improving Content Quality

Quanchen Liu*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This study addresses the ambiguous impact of AI tools on writing burden and content quality in AI-aided writing. Despite their potential benefits, existing research presents conflicting results and neglects content quality assessment. We aim to design and evaluate AI-aided writing artifacts that enhance content quality without increasing writing burden, focusing on recipe writing. Employing extended mind theory and design science research, we develop a comprehensive framework for designing AI-aided recipe writing artifacts. This framework encompasses meta-requirements, design principles, design features and evaluation metrics. Our research can contribute valuable design knowledge to writers, readers, and AI tool developers, promoting the effective utilization of AI-aided writing tools while balancing quality improvement and writing burden reduction.
Original languageEnglish
Title of host publicationSIGHCI 2024 Proceedings
Number of pages6
Place of PublicationAtlanta, GA
PublisherAssociation for Information Systems. AIS Electronic Library (AISeL)
Publication date2025
Article number20
Publication statusPublished - 2025
EventThe 23rd Annual Pre-ICIS Workshop on HCI Research in MIS - Bangkok, Thailand
Duration: 15 Dec 202415 Dec 2024
Conference number: 23
https://sighci.org/conferences/2024-pre-icis-workshop/

Conference

ConferenceThe 23rd Annual Pre-ICIS Workshop on HCI Research in MIS
Number23
Country/TerritoryThailand
CityBangkok
Period15/12/202415/12/2024
Internet address

Keywords

  • Design science
  • User burden

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