Artificial Intelligence for Academic Libraries
Clifford B. Anderson and Douglas H. Fisher. Artificial Intelligence for Academic Libraries. New York, NY: Routledge, 2025. 236pp. $48.99. Paperback. ISBN: 9781032680354.
Artificial Intelligence for Academic Libraries is a short introduction to the world of AI and Machine Learning (ML), especially as it relates to and will impact academic libraries. The intended audience of the book is academic librarians, as the very literal title suggests. However, the authors believe it would be of interest to others with concerns for AI in the academic setting.
Over ten chapters, the authors discuss the history, theory, philosophy, societal concerns, and the potential future of AI systems. The first three chapters lay the groundwork for the topic by giving a history of AI and a brief overview of the many iterations and types of AI. Helpfully, for those not deep in the field of AI and computer science, there are definitions and explanations throughout this section that come in handy for later chapters when an understanding of terms and acronyms is expected. Chapter one is a survey of AI and provides a roadmap of what is to come in the rest of the book. Chapter two is a history and discussion of deliberative (symbolic) AI. Continuing the story, chapter three is a history of connectionist AI, which is the type of AI that is currently on the ascendancy with large language models (LLMs) programs like ChatGPT and MidJourney.
Chapters four and five move the conversation in a different direction to discuss the philosophical, ethical, and societal concerns of AI. Chapter four discusses two well-known tests of AI to determine its intelligence level in relation to human intelligence, including the “imitation game” of Hollywood fame from the 2014 movie starring Benedict Cumberbatch. The authors offer this ominous warning for information professionals: “If artificial intelligence displaces expert human judgment in popular opinion, then librarians, along with myriad other experts, may find patrons actively bypassing them in favor of the oracles of bots” (63). Chapter five discusses ethics and societal concerns and is the largest in the book. It works its way up from Issac Asimov’s “Three Laws of Robotics” to modern-day concerns with the growing prevalence of AI systems. Of particular concern to librarians is the misinformation and biases found in AI, although environmental impacts are also discussed.
Chapter six moves the conversation into the practical realm of scholarship and AI use by students. The authors discuss how AI can be used (or not) to improve resource discovery, the peer review process, AI-human collaboration, and creating charts and figures. The sentiment of every area they look at is that AI is “currently failing to meet these [scholarly] norms” (112). The implications of this chapter also apply to student work and how students can use or abuse AI assistance, but a subsection concerns how teaching college composition may need to adapt. Similarly, their conclusions are that learning writing is fundamental to critical thought, and AI cannot take over this aspect of scholarship.
Wrapping up the book, the final four chapters also address real-world concerns. Chapter seven discusses “hybrid AIs,” or how various forms and modes of AI can work together to improve accuracy in outputs. Chapter eight focuses on the conversational aspect of AI and ways to improve both its effectiveness and its safety. Chapter nine, entitled “Professional Development,” focuses on what librarians can do to be better equipped to use AI and level up their skills, and the ways AI can be used to support professional development, such as grant writing. Finally, chapter ten moves the discussion of professional development forward with a look into potential future changes. The authors end on a positive note, encouraging librarians to take an active role at the center of AI discussions in the academy and their circles of influence.
Each chapter ends with a section of questions and activities for reflection. Presumably, this book will mostly be read by individuals, and these questions provide an opportunity for deeper thinking and practical engagement with AI. However, they also provide the opportunity for groups and colleagues to use this book in a book club fashion and engage with the material together, although the discussion questions and activities could take hours or even days to research and complete.
The strength of the book lies in the ground that it covers. The authors state they have four goals in writing the book: increase readers’ comfort with AI, increase professional development for academic librarians, increase librarians’ ability to evaluate AI platforms, and look to the future to help librarians anticipate coming changes (14). In this, they are successful and are able to explain things to a non-computer science, technically inclined audience. However, the book is still dense with the technical examples given, and there are a host of acronyms and concepts discussed that a basic background of AI would help the reader with understanding. Helpfully, the book is well-cited and ends with a 20-page bibliography.
One drawback of the work is the difficulty of publishing a book in a field that is so fast-moving. Op-eds and examples quoted are sometimes two or more years old. A new development in 2025 is the agentic AI Comet browser by Perplexity. This would change their chapters on agentic AI and professional development.
The book is written in a very straightforward manner and is full of examples and practical applications for librarians. The authors provide a balanced view of AI and present many sides to the debate of how AI is and will continue to impact libraries and librarians. I recommend this book for academic librarians based on the history, background, and definitions/acronyms it gives. The authors also move the conversation beyond the media hype, providing depth and context to the conversation that librarians are having around AI.