Five Upcoming Academic Books on Data Work, Big Tech, and Misinformation
Our most hotly anticipated books for fall!
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Posted on December 19, 2025 in Blog Posts
Authors:
LibTech Insights editor
It was a big year for LibTech Insights! We celebrated our third anniversary in January, and worked hard to keep growing, with new webinars on AI tools and Indigenous data sovereignty, a micro-course on AI literacy, and a partnership with the Ontario Council of Research Libraries. Of course, at the heart of what we do is showcasing the projects, tips, and thoughts of librarians who engage with technology in creative and interesting ways, and we’ve been excited to provide a platform for writers to share their findings. (Interested in contributing yourself? Just email us.)
We wanted to wrap up the year by highlighting some of the most buzzworthy (is this still a term?) pieces from the past year. We should note that we love all our posts equally, and we encourage you to page through our archive during any lulls in winter festivities—you’ll be delighted by what you find.

“Back in our college days, we millennials suffered article after article that tried desperately to understand who we were as a generation. They were full of generalizations, inaccuracies, and manic attempts to explain an apparent obsession with avocado toast. That kind of pandering web content was misguided at best and highly irritating at worst.
“Anyway, now it’s my turn to do that to the next generation.”

“At a high level, AI research assistants are tools designed to support and streamline the research process by automating tasks. A variety of AI tools are commonly lumped into this group, including AI-assisted citation generators, research summarization, document querying or ‘chat with document’ tools, research organizational dashboards or workflow automation, and data analysis or coding tools. However, within academic libraries, there is a need to consider AI tools in more nuanced ways—grouping these technologies by core function rather than their full range of potential uses. In this article (and based on how our vendors conceptualize the space), ‘research assistants’ are defined here as tools that support the research process through the AI-assisted discovery or mapping of existing knowledge. […]
“This blog post provides an overview of five popular tools available today, their strengths and gaps, and how you might use them in your own work.”

“We knew we needed to act, and it was clear that something needed to be done to engage fellow colleagues about AI. Though what that ‘something’ could be sparked so many ideas for action that any individual’s possible bandwidth might not be enough to tackle it. For all of our sakes, we were able to find each other and come up with some ideas, one of which was a community of practice. A community of practice offered a collaborative, low-barrier way to learn, experiment, and lead together in this evolving frontier.”

“Now, with the widespread use of GenAI tools, another layer has been added to already-packed one-shot sessions. The librarian’s role has expanded: it’s not just about finding and evaluating information, but about examining how knowledge is generated and shaped by artificial intelligence. In one-shot instruction, this adds both a challenge and an opportunity: how do we meaningfully incorporate GenAI instruction without sacrificing foundational research skills?
“The answer lies not in creating separate tracks for ‘AI literacy’ and ‘traditional library skills,’ but in integrating them. AI can be positioned as one step in the research process: useful for brainstorming, outlining, or identifying gaps in student understanding, but never a substitute for critical source selection or academic rigor.”

“In the world of libraries, every dollar matters. As budgets tighten and the demand for new services and resources increases, resource allocation increasingly becomes a complex and high-stakes puzzle. This is the question that keeps administrators up at night: Which projects will deliver the greatest return on investment for our patrons, and how do we fund them responsibly?
“Much too often, these critical decisions rely on intuition or historical spending. But what happens when you could eliminate the guesswork and use hard data to find the best combination of projects within a fixed budget? This is where Excel Solver comes in.
Our most hotly anticipated books for fall!
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Insights and best practices for teaching AI literacy to history students
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What our micro-course participants had to say about AI in libraries
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