Exploring ethical considerations in AI-driven cataloguing and classification with ChatGPT

Abstract

Purpose. This study investigates the ethical dimensions surrounding the use of AI-driven cataloguing and classification systems, exemplified by ChatGPT, in library sciences. The research aims to fill a gap in the existing literature by exploring privacy, accountability, transparency, and bias issues associated with these technologies. Design/Methodology/Approach. The study employs a comprehensive literature review to analyze the current landscape of AI applications in libraries, emphasizing ethical considerations. It also assesses existing guidelines from associations like ALA and IFLA, and explores privacy concerns, biases, and the impact on job satisfaction. Findings. The study identifies gaps in current ethical frameworks and emphasizes the need for guidelines to evolve with technological advancements. Privacy concerns, biases in AI outputs, and challenges related to user trust and transparency are highlighted. The impact of AI on job satisfaction for librarians is discussed, acknowledging both opportunities and challenges. Originality/Value. This study contributes to the broader discussion on ethical AI by specifically addressing the underexplored area of AI-driven cataloguing and classification systems. It underscores the importance of aligning AI use with ethical standards, proposing strategies for mitigating biases and fostering user trust.