Factors affecting the use of artificial intelligence generated content by subject librarians: A qualitative study

Abstract

To explore the factors affecting the use of artificial intelligence generated content (AIGC) by subject librarians through understanding their perceptions of AIGC. Interpretive phenomenological analysis (IPA) and technology acceptance model (TAM) were used in semi-structured interviews to explore the external variables of perceived ease of use and perceived usability of AIGC application in subject librarians. The perceptions of subject librarians towards AIGC included performance, risk perceptions, ability enhancement, and affective attitude. Attentions were paid to AIGC's performances in providing customized services, optimizing collection resources and improving cost efficiency. The risk perception involved technical stability, data security, user acceptance and occupational risk, the ability enhancement involved the improvement of personal literacy, innovative ability, and self-confidence through the use of AIGC technology, and the affective attitudes included not only excitement and anticipation for the technical potential of AIGC, but also concerns and skepticism about it, and critical attitudes toward its application in academic settings and the ethical issues it may raise. TAM analysis on the factors affecting the use of AIGC by subject librarians indicates that the external influencing factors of perceived ease of use include personal literacy, innovative ability, self-confidence enhancement and affective attitude; the external influencing factors of perceived usability include precise service, collection resource optimization, cost-effectiveness, technological risk, user acceptance and occupational risk. These factors constitute a theoretical framework for understanding and promoting the acceptance and effective use of AIGC by subject librarians. TAM analysis combined with IPA exploration on the external variables of perceived ease of use and perceived usability of AIGC application can identify the key factors affecting subject librarians' perceptions of AIGC, propose strategies for optimizing librarians' roles, enhancing information recognition ability and privacy protection, thus providing guidance for effective use of AIGC in library.

Keywords: Artificial intelligence generated content; Influencing factor; Interpretive phenomenological analysis; Subject librarians; Technology acceptance model.