Editorial

Evidence Summary Theme: Artificial Intelligence

Heather MacDonald

Associate Editor (Evidence Summaries)

Health and Biosciences Librarian

Carleton University

Ottawa, Ontario, Canada

2024 MacDonald. This is an Open Access article distributed under the terms of the Creative Commons‐Attribution‐Noncommercial‐Share Alike License 4.0 International (http://creativecommons.org/licenses/by-nc-sa/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly attributed, not used for commercial purposes, and, if transformed, the resulting work is redistributed under the same or similar license to this one.

DOI: 10.18438/eblip30574

We have all heard about ChatGPT by now. Artificial intelligence (AI) and machine learning (ML) are realities that libraries are coming to terms with. There are a number of good articles explaining what generative AI and ML are, their potential applications in libraries, and their challenges. But what does the research on AI with respect to libraries tell us? In this suite of Evidence Summaries, authors critically assess recent articles that consider different areas of libraries impacted by AI including collections, reference, information literacy, scholarly communications plus librarian perceptions of AI/ML. We hope you enjoy these ES and, possibly, find them useful in your own practice.