It's Academic

I recently had the opportunity to do an instruction session for a group of genealogists who were at the University of Pittsburgh (Pitt) as part of the GRIP Genealogy Institute. GRIP is an annual week-long in person learning practicum for dedicated genealogists who want to enhance their skills. I was first approached by professional genealogist and class organizer Sunny Morton about presenting in-depth academic history research to her researchers. I was initially hesitant to accept, but I’m glad I did!  

One reason for my hesitation is that as a liaison librarian, I very rarely handle genealogy questions. Since our Archives & Special Collections (A&SC) have an excellent Genealogy Research Guide, we usually direct any inquiries we receive to A&SC. We also have the excellent Documenting Pitt and Historic Pittsburgh sites, both of which have a wealth of genealogical research material. Given that the knowledgeable Carnegie Library Family & Local History Department is a short walk across Schenley Plaza from Pitt’s Hillman Library, I suspect many genealogists do their research there without ever contacting Pitt.  

Prior to my presentation to the group, Gena Philibert-Ortega did a presentation on Historical Context. In it, she encouraged the researchers to incorporate social history into their genealogy. Gena suggested that rather than genealogy being a collection of names and life events, it is at its best when it tells a story. To create that story, one must investigate the social, religious, economic, and political conditions that existed at a moment in the past. Gena demonstrated this by showing a picture of some female ancestors on a California beach and asked questions of it: What is this location? Why might the women have been there? What do the clothes they’re wearing tell us? I was delighted to hear this, because this is the type of thinking that Pitt history profs seek to inculcate in their students. Gena mentioned in passing Evidence Explained, which is a citation style for genealogists. I’m glad I know about that now! Gena concluded the session by showing the researchers how they could use Google Scholar and JStor without library access.  

In preparing for my presentation, one of my first concerns was getting the researchers temporary access to library-licensed eResources. We do offer one-day access to library databases, eBooks, and eJournals for patrons who come to the library and request a guest login. In the past, we’ve had large groups of non-Pitt affiliates show up to the library hoping to get that access; predictably, those instances were chaotic and unproductive. Fortunately, my A&SC colleague David Grinnell was able to work with library IT to get the researchers their codes before the class. The codes were good for their week on campus so they could continue their research while here. During my instruction session, walking everyone through the login process was more time-consuming than I had anticipated. The temporary access codes were random strings of letters and numbers, which made entering them tedious. There were also some system messages which happened during the process which I hadn’t anticipated. 

Given the GRIP researchers were on campus for only a week and were from all over the country, I decided to focus my presentation on the research materials and tools available at most academic research libraries rather than Pitt specifically. While I did show the researchers how to use our discovery layer PittCat, I emphasized that it’s an implementation of Primo, which is used by the majority of academic libraries. I also did demonstrations of my United States History Guide and America: History and Life. (I’ve always liked that database’s ability to search by time period discussed rather than simply publication date.) I concluded by showing the researchers ProQuest Dissertations and Abstracts. A couple of them were delighted to see a dissertation about the town they were researching. I was hoping to have further discussions of their research projects, but we simply ran out of time. Perhaps I’ll have an opportunity next year! Overall, I had a wonderful experience working with researchers from GRIP and will incorporate some of their primary source practices into my undergraduate history information literacy instruction. 

Like many library database collections, mine is centered around EBSCO. We have 28 different EBSCO databases for students to search within EBSCOhost Web, so any changes there have a big impact, and EBSCO has begun adding AI features to its products. There is a new “AI-Assisted Search” option that uses AI to enhance student search results. The latest try by EBSCO to have a Google-like search.

While that is interesting in itself, the features I’m more inclined to discuss are the AI Insights and Ask AI Features. Both of these offer enticing benefits to researchers while also having serious possible downsides for student learning.

Clicking the AI Insights link at the bottom of an article causes a summary of the article to be generated. The summary consists of four or five bullet points that cover key parts of the article. One would hope that these results are accurate because by integrating AI within our library collections we run the risk of allowing in the same inaccurate AI generate information we are trying to warn the public about. Libraries could become synonymous with “AI slop” if our offerings aren’t held to a high standard. I also can’t help but worry that students will avoid reading entire articles and instead rely on summaries. Real learning takes more than a few sentences. It takes some time for a new idea to cast its spell on you.

The AI Ask feature is more exciting. It allows the user to ask AI questions about the article itself. Is the methodology sound? What was the conclusion? How big is the sample size? I find this more beneficial to learning in that it requires the user to think actively to ask questions about the article. The AI becomes like a tutor explaining the article to a student. Of course, this does allow the student to bypass learning how to read complex texts. And the concerns about accuracy remain. Convenience has its price.

These new tools offer the same tradeoffs as other AI tools, convenience at the cost of trustworthiness. The possible replacement of human potential with AI. EBSCO allows these features to be turned on or off. Despite my misgivings mentioned above, I’ve decided to leave them on for now. It’s hard to resist the possibilities they bring.

As information literacy librarians, we’re accustomed to technology having an impact our teaching.  But gen AI has felt like a whole other ballgame with its rapid change and widespread impact.  Over the past few years, I’ve witnessed reactions to gen AI at both ends of the spectrum from outright rejection to uncritical adoption.  Where do we as information literacy instructors land on this spectrum?  And, most importantly, what do we teach our students about gen AI and the research process? 

In the Buddhist tradition, ‘the Middle Way’ refers to a balanced approach to life that avoids extremes in thought and action.  I would argue that many librarians teaching information literacy have been following a ‘middle way’ approach in response to new technologies for years.  With guidance from the ACRL Framework for Information Literacy for Higher Education, we teach about the authority concerns with Wikipedia while also explaining its usefulness as a research starter.  We explore the dangers of algorithmic bias in internet searching while also teaching students how to leverage Google results in the lateral reading/fact-checking process.  As information scientists, we are objective in our approach to technology and in our assessment of its impact on information and the research process.  We are not Luddites.  And we also don’t buy the AI hype.  I recently attended an ACRL CHOICE webinar,  “Genuine Learning in the Age of AI” and was encouraged to hear from scholars who are defining what it looks like to teach critical thinking and information literacy skills while using gen AI tools.  The panelists outlined approaches that emphasize critique, reflection, and reasoning while engaged with gen AI.  They advocated directing students to focus on the overarching question “Are you going to know when the AI is wrong?”   This emphasis on maintaining critical objectivity and developing information literacy skills while using gen AI charts a course for library instruction that avoids extreme reactions to this new technology.  

The Framework for Information Literacy was created to address the impact of emerging technologies on information and the research process and, even though written in 2015, it provides useful insight and guidance for analyzing gen AI tools.  The recent revision of the Framework for Information Literacy makes this application of the frames to gen AI tools even more explicit.  With the Framework and our perspective as information scientists, librarians are well-positioned to support students in the development of their critical thinking about gen AI tools and to define a ‘middle way’ for information literacy instruction.

As the Electronic Resource and Interlibrary Loan Librarian, I find myself being ghosted a lot.  And when I say “ghosted” I mean ghost citations and other AI hallucinations.  When I receive an interlibrary loan request (ILL), I always check the citation first for accuracy.  Thankfully, 98% of the time, these are correct and I can proceed with the request.  The other 2%?  That’s where the ghosts come in.

I’m thankful that ghost citations are not a huge problem at my university, however I see the potential for a host of problems in the academic world.  Over 10,000 peer-reviewed research papers were retracted due to AI fraudulency in 2023 alone (Yates, 2025).  If a trained researcher is having a hard time distinguishing real or fake information, how is a college student, new to research, going to know what to look for?   This is where academic librarians come in to save the day.  I like to think we have cool capes.

The world of research integrity is under attack from many fronts; we all see it in our everyday jobs.  Students are turning to AI to make their lives easier.  Research faster.  But, as information professionals, we need to teach them that easier and faster isn’t always going to give them the result they’re looking for, or at least what their professors want.  Going to college offers students the opportunity to be open to critical and creative thinking.  AI tends to dampen that.  A study out of MIT shows that 83% of students who use AI to help write their papers don’t remember what they read or wrote, because they lacked engagement in the assignment (More Curricular, 2025).

This next generation of students needs to be critical and creative thinkers, or the robots we fear may rule the world someday win.  We are human.  And humans need to use our brains.  Tease out the next problem.  Understand how to fix global warming.  Machines are not going to sustain us.  Only our living brains will.  I imagine our world becoming like the fictionalized story in Wall-E (which is my favorite Disney movie).  That story has the potential to come true, and that should scare us.  Living in a garbage infested environment.  No trees, no plants.  Living on a “cruise ship” in outer space.  Those people can’t even walk because they don’t use their muscles.  Seem familiar?  We can use machines to help.  To aid us.  But they should always be secondary to human thoughts, emotions, and creativity.

I’ll leave you with this.  We are at a precipice.  We have the potential to impact generations to come.  Why leave that to a machine?  Teaching our current students that they have the power to become amazing researchers, doctors, lawyers, scientists.  To use the beautiful brains we’ve been given.  What a waste to let AI “do the work.”  Teach our students to do the work.  To understand, to challenge what has and is being done.  That’s where innovation lies.  Let’s feed motivation to our students and give them practical tools to use in the real world.  Put on those librarian capes, challenge your students and watch Wall-E.

References

More Curricular (2026). The memory gap: why 83% of students can’t remember what they wrote with AI. https://www.morecurricular.co.uk/post/the-memory-gap-why-83-of-students-can-t-remember-what-they-wrote-with-ai

Yates, K. (2025). Citation cartels, ghost writing and fake peer-review: fraud is causing a crisis in science–here’s what we need to do to stop it. Live Science. https://www.livescience.com/human-behavior/citation-cartels-ghost-writing-and-fake-peer-review-how-fraud-is-causing-a-crisis-in-science-and-what-we-can-do-about-it-opinion