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The introduction of ChatGPT 3.5 in November 2022 ignited a sensation in the academic community, leaving many astounded by its capabilities. This new release more closely emulates human responses than its predecessors. Among its remarkable capabilities, it can answer questions, catalog items in MARC21, recommend reading lists, and make suggestions on a wide array of topics. To assess ChatGPT’s efficacy in aiding library users, the authors of this paper conducted an experiment comparing ChatGPT’s performance with that of librarians in answering reference questions. Thirty questions were randomly selected from the transaction log of the reference inquiries between June 1, 2023 to July 31, 2023 at the Rider University Libraries. These queries constituted 34% of the total user questions during this two-month period. The authors compared the answers by ChatGPT and those by reference librarians for their accuracy, relevance, and friendliness. The findings indicate that reference librarians markedly outperformed their robotic counterpart. An evident issue arises from ChatGPT’s deficiency in understanding local policies and practices. This consequently hinders its ability to provide satisfactory answers in those areas. OpenAI posits that ChatGPT’s proficiency can be enhanced through targeted fine-tuning using locally specific information. At the moment, ChatGPT remains a great tool for librarians. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is a defining technology of the 21st century, creating new opportunities for academic libraries. The goal of this paper is to provide a much-needed analysis, interpreted in an international context, on what the leaders of academic libraries in East-Central Europe, and specifically in Hungary, think about AI and its implementation in a library setting. The survey shows that according to library directors AI is more of an opportunity for academic libraries than a threat, and it could provide support in all areas of library operation, including digitising, information service, and education. Findings indicate that a quarter of the Hungarian academic libraries surveyed use AI-supported solutions, mostly in the areas of information retrieval and data processing. Using Rogers (The diffusion of innovations. 5th ed. The Free Press, 2003) diffusion of innovation model, it may be projected that an explosive growth is to be expected in the use of AI in libraries. [ABSTRACT FROM AUTHOR]

Automated indexing--using a computer to look at individual documents and assign metadata without a person looking at every document--was used to build an interactive online database to store and retrieve pages from a loose-leaf resource (i.e., a resource that changes state over time). A database was designed and more than 30,000 pages in the database were indexed. Digitization, optical character recognition, and computer scripting to extract metadata were the methods used to assign most metadata. In places where the computer program could not assign metadata, a person looked at the document and assigned metadata. The index was audited for errors. The computer script and the human indexer had comparable error rates but computer indexing spent much less time per value assigned. It is recommended that automated indexing be considered in indexing projects, especially where a large number of similar documents are to be indexed. [ABSTRACT FROM AUTHOR]