Artificial Intelligence for Libraries

Artificial Intelligence for Libraries Brady D. Lund Suggested Citation: Lund, B. D. (2025). Artificial Intelligence for Libraries. Bloomsbury. Abstract Artificial intelligence is an extremely important but little-understood topic, including in libraries. This timely book explores what AI is, how it works, how it's relevant to all types of libraries, and how it can be used. Readers will better understand the use of AI in library systems and applying AI to teaching and learning environments, and they will grow in the ability to discern potential ethical issues posed by this emerging technology. The final chapter provides a practical guide to using various types of AI in libraries. Table of Contents, Abstracts, and References List This file contains the description, table of contents, and complete list of references for the forthcoming book, Artificial Intelligence for Libraries, to be released this fall. Contact me for further details. Table of Contents Introduction 1 – What is AI? 2 – How AI Works 3 – AI Ethics 4 – A History of AI and Libraries 5 – Library Systems and AI 6 – AI Literacy 7 – AI for Teaching and Learning 8 – AI for Scholarly Publishing and Research 9 – Building AI Solutions for Libraries 10 – Our Next Generation of AI Libraries Index Abstracts Chapter 1: What is AI Artificial intelligence is a set of technologies with the potential to reshape society, politics, and economies at a scale that could easily rival the impact of the Internet. This introductory chapter outlines some fundamental questions about AI: its definition, functioning, applications, and associated risks. The societal impact of AI is discussed, along with the ethical considerations this technology poses, and the varied public perceptions of the technology influenced by demographics, employment, and political ideologies. As trusted community information centers, libraries play an important role in educating communities about the opportunities and challenges presented by the emergence of AI. This chapter sets the stage for our comprehensive examination of AI’s implications through emphasizing a balanced understanding, responsible use, and critical evaluation of emerging innovations. Chapter 2: How AI Works Abstract: The ways in which humans interact with technology are being revolutionized by the emergence of new developments in artificial intelligence, with language-based models standing out as one of the most transformative advancements. Understanding the technical foundations of these models is key to appreciating their potential and limitations. This chapter describes the core functionality of computers and algorithms, laying the groundwork for understanding AI architectures. Through an exploration of various programming and computer science principles’ role in AI development, this chapter illustrates how language models translate human commands into machine-executable instructions. The process of training AI models is then discussed, emphasizing the importance of data diversity and parameter adjustment to optimize performance. Testing methodologies, including pre-training and fine-tuning, are highlighted to ensure coherence and task-specific excellence in AI outputs. Case studies on GPT-1 and GPT-4o demonstrate the evolution of language models, showcasing advances in data processing, training scale, and architectural complexity. Chapter 3: AI Ethics While artificial intelligence technology is evolving rapidly and integrated across various facets of society, it raises immense ethical issues that must be addressed to ensure that it is used in ways that are both responsible and fair. This chapter investigates seven key areas of ethical concern raised by the emergence of AI: transparency, fairness, accountability, privacy, security, usercentered design, and environmental sustainability. The risks posed by AI are discussed, including model bias, data misuse, security vulnerabilities, and the environmental toll of its computational demands. Efforts at federal and local levels to govern AI development and use, such as the Biden-Harris Administration's Executive Order 14110, are presented as some initial steps in addressing these ethical issues. The chapter underlines the leading role that information professionals can play in promoting the diffusion of ethical AI through education of general audiences and ensuring innovation comes with a sense of responsibility. Chapter 4: A History of AI and Libraries Over the past century, artificial intelligence technology has evolved tremendously, beginning as merely a conceptual notion and establishing itself today in the form of sophisticated technologies such as large language models and chatbots like ChatGPT. By understanding the historical development of artificial intelligence, we can better grasp both its current possibilities and future trajectory. This chapter provides a scoping overview of nearly one hundred years of technological progress, tracing AI's trajectory from its first conceptualization through its modern intersections with librarianship and information science. Distinct “eras” are discussed that have shaped the field of AI, highlighting milestones from early 20th-century pre-information science breakthroughs to today’s AI-driven paradigm shifts. Chapter 5: Library Systems and AI Library systems development may be tremendously impacted by the emergence of new artificial intelligence tools that position themselves to enhance both system efficiency and user experience. This chapter explores the potential of AI-powered system in libraries, while emphasizing its role in augmenting, rather than replacing, the work of professional librarians. The chapter highlights key areas where AI can streamline operations, such as automating tasks like acquisitions and classification, and enhancing patron services through tools like chatbots, smart search functionalities, and content summarization. Emerging applications, including Retrieval-Augmented Generation, early detection systems for student support, and AI-driven translation tools are explored. Chapter 6: AI Literacy New competencies are required in order to navigate the technological complexities presented by artificial intelligence’s new major role in the digital age. AI literacy, built on foundational literacies such as data and algorithmic literacy, can empower individuals to engage critically with AI technologies while recognizing these technologies’ risks and limitations. This chapter examines the growing importance of AI literacy as a core competency for information professionals. The chapter underscores the need for critical evaluation and source verification when interacting with dynamic AI models like ChatGPT. Key components of AI literacy, including understanding data and algorithms, identifying biases and ethical challenges, and combating misinformation, are discussed. Practical strategies for teaching AI literacy among librarians are provided. Chapter 7: AI for Teaching and Learning Teaching and learning may be dramatically transformed by the emergence of new artificial intelligence tools in coming years. This chapter explores how AI is being integrated into classrooms to shift pedagogy through innovations such as adaptive learning systems, personalized AI tutors, and enhanced learning analytics. While these developments offer significant benefits, they also raise ethical and practical concerns, including the potential misuse of AI in academic work, the challenges faced by educators in adapting to rapidly changing technology, and the impact of AI tools on student learning outcomes. The chapter examines these issues, providing insights into how educators can use AI to improve lesson planning, foster student engagement, and uphold academic integrity. It also highlights the importance of staying informed about technological advancements and establishing clear policies for the responsible use of AI in education. Chapter 8: AI and Scholarly Publishing Scholarly publishing has historically faced a large number of challenges and paradigm shifts that threaten its legitimacy, including controversies over plagiarism, editorial standards, and emerging technologies. The rise of generative artificial intelligence represents perhaps the most substantial challenge to date. This chapter examines implications relating to AI's role in scholarly publishing, discussing key concerns such as whether AI can be considered an author and its impact on the integrity of published works. While generative AI offers many possible benefits, such as improving the accessibility of research for non-native English speakers, it also presents several risks, including the creation of fictitious content and unacknowledged authorship. The chapter discusses the important balance between innovation and ethical standards for AI in publishing, discussing how generative AI might reshape scholarly publishing in the future, while highlighting the importance of transparent and responsible use. Chapter 9: Building AI Solutions for Libraries Artificial intelligence has the potential to reshape library services by offering innovative tools to enhance services and operational efficiency. This chapter provides a practical guide for developing some of these innovative AI solutions across library contexts, focusing on three key applications: a library reference and directional support chatbot, an image classifier and text recognition tool, and a fine-tuned language model for supporting scholarly writing. Employing the Python programming language, readers are guided step-by-step through the process of building these tools while addressing integration challenges within library contexts. By building on the ethical considerations for AI discussed earlier in the book, the chapter highlights practical issues in AI tool deployment, such as operational challenges and understanding AI models. Strategies for overcoming these barriers and ensuring smooth implementation are discussed. Chapter 10: Out Next Generation of AI Libraries Abstract: Artificial intelligence is transforming industries worldwide, and as demonstrated throughout this book, its influence on libraries is certainly no exception. An understanding the multifaceted impact of AI on library services, ethics, and research is critical for sustaining libraries’ relevance in the age of AI. This concluding chapter emphasizes the need for library and information professionals to assert leadership in AI literacy and technology management, drawing upon their expertise in information ethics and digital literacy. 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