by Rafia Mirza In our research technology workshop series at my home institution we discuss not only the technical skills that go into a project, but also the ethical considerations as well. In our workshops we often start with the conceptual questions-why might you do something a certain way-before we focus on the how. We…

by Sharon Clapp In the discipline of artificial intelligence (AI) known as machine learning (ML), “supervised learning” takes place when a set of data that has already been classified by humans is used to “teach” the machine how to classify additional data on its own. While it is underpinned by a lot of math and…

by Robert Wilson In January 2022, my role changed to Systems and Analytics Librarian at Middle Tennessee State University’s Walker Library. In this role, time is dedicated to reporting including the formalization and automation of past data analytics and data visualization work as well as predictive analytics. This work includes improving and automating descriptive reports…

by Thomas (T.J.) Ferrill It was such a privilege to have been invited to participate as a fellow in the 2022 IMLS IDEA Institute on AI. Learning alongside researchers, practitioners, and scholars working in library and information science was an unparalleled opportunity to consider the impacts of AI on library workflows at many levels. Broadly…

by Borui Zhang Hi, IDEA blog site visitor! I’m an “AI librarian” I’m a human being too – sorry if I disappointed you. I work as the NLP specialist at my school library where we provide AI consultations, training, and resources to students, faculty, and staff. (“AI librarian” is the nickname my colleague gave me.)…

By Daniella Smith Connecting AI and ML to Libraries I am very appreciative for the opportunity to attend the IDEA Institute. It has been wonderful listening to the ideas about applying Artificial Intelligence (AI) and Machine Learning (ML) to librarianship. Often, people do not associate librarianship with AI and ML. However, the disconnect is a misconception.…

by Lencia Beltran The Artificial Intelligence application of machine learning predictive analytics and recommender systems is pervasive in a number of companies today like Amazon, Spotify, and Pinterest, but what about libraries? It’s unlikely a person will see or have heard of such systems being widely used in many Libraries, even though they can offer…

by Mary Beth Holm AI is already a major part of everyday life, whether people are aware of it or not. Credit, healthcare, career opportunities, and even personal freedom may be impacted by AI. It is important that people understand AI and that there are equitable opportunities to work with AI and machine learning. This…

by Erik Radio Iterative processes constitute a significant part of any machine learning (ML) project. For my project I found they were necessary even before arriving at any coding. Specifically, just the concept and telos of ML changed the ways in which I thought about a particular problem. ML let me hone in on larger…

by Valerie Lookingbill With the exponential rise in online publishing, there is an increasing need for comprehensive overviews of research, including systematic reviews, a methodology for conducting reviews of literature that prescribes explicit, reproducible, and transparent processes for collating the best available evidence on a particular topic. While this rise in publications presents opportunities for…