Abstract：The rise of AIimplications and applications of artificial intelligence in academic libraries The Rise of AIImplications and Applications of Artificial Intelligence in Academic Libraries is a curated collection of essays from LIS scholars and practitioners on the impact and applications of AI in academic librariesThis is a timely publication considering that in 2019experts anticipatedAI in education to grow by 43in the period 20182022Zawacki-Richter et al20191If the emergence and widespread adoption of large language modelsLLMslike OpenAIs ChatGPT is any indicationacademic libraries need to be both reactive and proactive with regard to the various opportunities and challenges that AI offers on areas such as information generationdiscoveryand management of systems and processes within higher education in general and libraries specificallyThe book is organized into three partseach focusing on a different aspect of artificial intelligence and machine learning within the academic library contextThe first partcomprising of eight chaptersfocuses on user services and front-line programmingWhile the examples of library programming in this section can certainly inspire librarians as academic libraries face the challenge of addressing the place and usefulness of artificial intelligence in the higher education contextmost of the chapters in part 1 are largely descriptivethey outline the details of particular programming choices and the specific outcomes of the programming offeringsChapter 4titledIncubating AIThe collaboratory at Ryerson University Libraryis a notable exception to thisas it outlines best practices that emerged as a result of the case studies presentedWhile the other chapters in this section do include reflections on their particular challengesmost do not distill their conclusions beyond the particulars of narrowuniqueand specific case studieswhereas there may be room for such presentations at specialized conferences or symposiaa volume like this would have benefitted from the sort of generalized advice presented in chapter 4Part 2 discusses issues around collections and discoveryAll six chapters in this section touch on interesting problems facing academic librariessuch as the utility of artificial intelligence and machine learning in image cataloguing in both library and non-library contextsAI enhancements geared toward searchabilitythe benefits of automationthe training of staff regarding machine learning functionalitycomputational approaches to handwritten text recognitionand the translation of academic articles into non-scientific vernacular for the purposes of knowledge disseminationMost studies in part 2 include general discussions of the practices under investigationwhich makes much of the content in part 2 adaptable across various institutional contextsMoreoversome chapterschapter 7titledSubjectivity and discoverabilityAn exploration with imagesbeing a great example of thisafford the reader a glimpse into the future automation of some library work that has heretofore been only imaginable as human labourThis content is particularly interesting because it challenges the supposed fixity of librarian identityKlein and Lenart 2020Part 3 focuses on future applicationsand while the content in this section is more theoreticalthis sectionconsisting of only two very short conceptual papersis unfortunately somewhat underdevelopedNeverthelesswhat the reader will find here contains both value and utility for academic librarians working on shaping their professional practice in ways that will allow them to tackle both current and future challenges and opportunities of AI and machine learning in librariesFor examplethe excellent first chapter in this sectionchapter 13titledEthical implications of implicit bias in AIImpact for academic librariesexploresethically problematic outcomes in academic libraries179such as the problem with dataset bias and the potential for the magnification of prejudices and stereotypesThis is the kind of work that will benefit libraries and librarians in the coming yearseven as the artificial intelligence and machine learning landscape continues to changeThe inclusion of this chapter is both important and well placedMore chapters like this one should have made it into this volume as a means of framing and synthesizing contributions in the other two sections of the bookContemplations of this sort could have been used throughout this edited volume as philosophically and theoretically grounded introductions to the content outlining the practical challenges of the purely descriptive chaptersOverallthe chapters that offer most value and utility in this collection are the ones that contain more general and philosophical discussions around automationartificial intelligencemachine learningand so onThe reason those selections are so outstanding is that the field evolves and changes at an exponential pacemeaning that a book which mostly focuses on examples without the benefit of some theoretical musings and considerations of best practices aimed at future trends is outdated almost as soon as it is publishedThe more an example relies on the peculiarities of an individual institution or organizational circumstances of a particular librarythe less application and adaptability such examples containand the quicker they become obsolete as technology continues to change and emergeHoweverwhat shines through in this collection are the pieces of advice and thoughtful considerations that transcend the programming choices and special circumstances faced by libraries with unique organizational structuresresourcesand issuesas those more generally applicable contributions will be of lasting valueLibrary AutomationThe article mentions the automation of library work through AI and machine learningespecially related to image and handwriting text recognitionCollection ClassificationThere is mention of AI and machine learning applications in image catalogswhich may be related to collection classificationRetrieval and IndexingThe article mentions AI enhancing search capabilitieswhich is related to retrieval and indexingNLPThe article mentions Large Language ModelsLLMssuch as OpenAIs ChatGPTwhich are primarily used for language processing and generationMachine LearningThe article discusses multiple chapters on how machine learning is applied in librariessuch as image catalogsenhanced search capabilitiesand handwriting text recognition