Student-created media: Designing research, learning, and skill-building experiences

Abstract

metadata and scholarship discoverability, a machine learning club for information specialists, handwritten text recognition (HTR) technologies to support research, and using IBM Watson through a library-industry partnership are some of the case studies that comprise this section of the book. Part III, “Toward Future Applications,” contains two chapters that focus on the ethical implications of implicit bias in AI and its impact for academic libraries, and machine information behavior and AI-authorship. This book features a comfortable balance between theoretical and practical application of AI concepts and tools. For instance, Chapter 8’s discussion of Doc2Vec and DBPedia software to enhance metadata discoverability and inform human metadata creation within electronic theses and dissertations (ETDs) is highly informative and relatable. In addition, Chapter 4’s description of empowering graduate students and researchers through interdisciplinary AI projects and the opening of a Collaboratory incubator space within the Ryerson University Library is a strong example of partnership, collaboration, and interdisciplinary support. Overall, this volume is a great book of case studies for experimentation and implementation of AI endeavors within academic libraries.