This issue of Library Technology Reports argues that the near future of library work will be enormously impacted and perhaps forever changed as a result of artificial intelligence (AI) and machine learning systems becoming commonplace. It will do so through both essays on theory and predictions of the future of these systems in libraries and also through essays on current events and systems currently being developed in and by libraries. A variety of librarians will discuss their own AI and machine learning projects, how they implemented AI and to what ends, and what they see as useful for the future of libraries in considering AI systems and services. First up is an essay relating the development and design of a machine learning system developed by a library and deployed to production in a library anywhere in the US. The system is HAMLET (How about Machine Learning Enhanced Theses) by Andromeda Yelton, currently a developer at the Berkman Klein Center for Internet and Society at Harvard. At MIT, she created and developed HAMLET. Next, in chapter three, we have an essay by Bohyun Kim, CTO and associate professor at the University of Rhode Island Libraries, where she discusses the launch of their Artificial Intelligence Lab, which is housed in the library on campus. Then in chapter four, Craig Boman, Discovery Services Librarian and assistant librarian at Miami University Libraries, looks at his attempts to use a type of machine learning to build a system to assign formal subject headings to unclassified, full-text works. This report will conclude with a discussion of possibilities and potentials for using AI in libraries and library science.
This issue of Library Technology Reports argues that the near future of library work will be enormously impacted and perhaps forever changed as a result of artificial intelligence (AI) and machine learning systems becoming commonplace.
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Current State of AI Technology |
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Chapter 2 HAMLET: Neural-Net-Powered Prototypes for Library Discovery |
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How HAMLET's Neural Net Works |
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Neural Nets and Traditional Metadata |
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Chapter 3 AI and Creating the First Multidisciplinary AI Lab |
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Why Does Artificial Intelligence Matter? |
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AI Lab at the University of Rhode Island |
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Chapter 4 An Exploration of Machine Learning in Libraries |
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Recommendations for Future Research |
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Chapter 6 Sources Consulted |
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Jason Griffey is an associate professor and head of library information technology at the University of Tennessee at Chattanooga. His latest book, Mobile Technology and Libraries, is now available as a part of Neal Schuman's Tech Set. Jason's previous book, Library Blogging, with Karen A Coombs, is available through Amazon. He can be stalked obsessively at www.jasongriffey.net and at Pattern Recognition, his personal blog. He is the author of the American Libraries Perpetual Beta blog, and is also a columnist for the ALA Techsource blog. Jason was named one of Library Journal's Movers and Shakers in 2009 and is regularly invited to speak on libraries, the social economy, mobile technology, and other technology-related issues. He spends his free time with his daughter, Eliza, reading, obsessing over gadgets, and preparing for the inevitable zombie uprising.
