@article{ART003279062},
author={Lee, Jeong-Mee},
title={Exploring Data Bias and Mitigation Strategies in Generative AI-Driven Library Service Environments},
journal={Journal of the Korean Biblia Society for Library and Information Science},
issn={1229-2435},
year={2025},
volume={36},
number={4},
pages={183-205}
TY - JOUR
AU - Lee, Jeong-Mee
TI - Exploring Data Bias and Mitigation Strategies in Generative AI-Driven Library Service Environments
JO - Journal of the Korean Biblia Society for Library and Information Science
PY - 2025
VL - 36
IS - 4
PB - Journal Of The Korean Biblia Society For Library And Information Science
SP - 183
EP - 205
SN - 1229-2435
AB - This study examines the impact of Artificial Intelligence (AI) technologies on library environments and provides an in-depth analysis of the ethical challenges and issues—particularly data bias—that library information services face in the AI era. By synthesizing and critically reviewing a broad body of literature, the study offers insights into the roles that libraries and librarians must assume to address these challenges and presents recommendations for the strategic transformation of library information services. The research addresses three key questions: (1) how AI technologies are transforming core library services; (2) what ethical issues emerge throughout this transformation; and (3) how to present strategic and policy directions for the stable implementation of AI technologies in library service environments. Based on this analysis, the study proposes directions for the strategic role transition of libraries and information professionals to ensure the responsible and stable integration of AI technologies into library service environments. The findings emphasize that libraries must move beyond the passive adoption of AI and position themselves as responsible agents in addressing ethical issues arising from AI-driven systems. The study highlights the growing importance of critical literacy within increasingly diversified literacy education frameworks and underscores the need for a comprehensive ethical governance structure - including clear guidelines and algorithmic auditing procedures - across all stages of AI implementation.
KW - Generative AI;Data Bias;Information Services;Critical Literacy;AI ethics
DO -
UR -
ER -
Lee, Jeong-Mee. (2025). Exploring Data Bias and Mitigation Strategies in Generative AI-Driven Library Service Environments. Journal of the Korean Biblia Society for Library and Information Science, 36(4), 183-205.
Lee, Jeong-Mee. 2025, "Exploring Data Bias and Mitigation Strategies in Generative AI-Driven Library Service Environments", Journal of the Korean Biblia Society for Library and Information Science, vol.36, no.4 pp.183-205.
Lee, Jeong-Mee "Exploring Data Bias and Mitigation Strategies in Generative AI-Driven Library Service Environments" Journal of the Korean Biblia Society for Library and Information Science 36.4 pp.183-205 (2025) : 183.
Lee, Jeong-Mee. Exploring Data Bias and Mitigation Strategies in Generative AI-Driven Library Service Environments. 2025; 36(4), 183-205.
Lee, Jeong-Mee. "Exploring Data Bias and Mitigation Strategies in Generative AI-Driven Library Service Environments" Journal of the Korean Biblia Society for Library and Information Science 36, no.4 (2025) : 183-205.
Lee, Jeong-Mee. Exploring Data Bias and Mitigation Strategies in Generative AI-Driven Library Service Environments. Journal of the Korean Biblia Society for Library and Information Science, 36(4), 183-205.
Lee, Jeong-Mee. Exploring Data Bias and Mitigation Strategies in Generative AI-Driven Library Service Environments. Journal of the Korean Biblia Society for Library and Information Science. 2025; 36(4) 183-205.
Lee, Jeong-Mee. Exploring Data Bias and Mitigation Strategies in Generative AI-Driven Library Service Environments. 2025; 36(4), 183-205.
Lee, Jeong-Mee. "Exploring Data Bias and Mitigation Strategies in Generative AI-Driven Library Service Environments" Journal of the Korean Biblia Society for Library and Information Science 36, no.4 (2025) : 183-205.
