Oh, look, the thing that librarians have been warning you about since 2023! www.insidehighered.com/news/faculty...
06.03.2026 13:34
👍 0
🔁 0
💬 0
📌 0
Oh, look, the thing that librarians have been warning you about since 2023! www.insidehighered.com/news/faculty...
Well, a wife-abusing cannibal ex-boxer told us we were all fat on behalf of RFK Jr, and Amazon tried to sell us surveillance tech on the backs of missing puppies, so the race to the bottom is competitive, but the AI ads have been more than up to the task.
Here’s another pretty good one on NotebookLM and summarization. dl.acm.org/doi/pdf/10.1...
bsky.app/profile/drum...
You had the same thought as I did! I explained what I found above.
By November 2023, it included the 2020-2022 run, including the article that Jill linked. Not a sure thing that AI was involved (other citations in this article are sloppy, but not necessarily AI), but, despite claimed publication date, it wasn't on the site until months after ChatGPT came out. end/
There aren't Wayback-archived versions of the article or volume/issue, but there's an archived version of the publication archive. Here's the weird part - by September 2022, the publication archive was out of order and didn't have any volumes published after 2020. 4/
Anyway, after I did some checking on the article that Jill linked (mixed results--journal isn't in Ulrichs Periodical Directory, but the credited authors are affiliated as described), I used the Internet Archive Wayback Machine to see when this article actually showed up . . . 3/
For instance, about a year ago, we found a publisher that populated their archive with a bunch of back-dated abstracts that were almost certainly all AI-generated. It lent them an air of legitimacy presumably so that their more recent, low-quality articles had some weight to them. 2/
Academic librarian here and my colleagues and I have done some work on instances like this. A tricky thing about sketchy publications is that you often can't trust dates. This article may have a 2021 data on it, but that doesn't mean it's actually been around since then. 1/
I checked through some of the other citations, as well. Most are either legit or only contain minor issues that are pretty common human goofs, like this one (wrong volume/issue, wrong page numbers), but there are some odd things about this article/journal that I'll post further up.
The upshot is that we were able to knock results from the journal out of our article search and got the publisher's journals removed from Ulrich's. But this is clearly going to be an eternal game of Whac-a-Mole for librarians (and for patrons who contact us to report this stuff)! 4/4
In another, a student found an article that had seemingly AI-generated fake citations using our institutional article search (which searches our subscription stuff, but also beyond). It got picked up via CrossRef. Another sketchy publisher, but this one with enough oomph to be listed in Ulrich's. 3/
In one, a researcher told us he'd found himself cited as coauthor on a paper he hadn't written. We found a few years' worth of backlog on the journal's page (hijacked version of a legit journal) was AI-generated abstracts and titles to pad things out for the newer, dubious full-text articles. 2/
My colleagues and I (librarians at UW-Madison) just ran a two-hour presentation on the impact of gen AI on predatory publishing for library staff this week! It was directly inspired by a few patron interactions similar to what you're describing. 1/
My bandmates and I were *really* into that show. A few years later, a club offered my ex-bandmates' new band an opening spot for either Flickerstick or the Arcade Fire, who were just about to receive their Pitchfork 10.0 for Funeral. Guess which show my friends picked . . .
1. The DOJ has sent threatening letters to several medical journals, focused around whether these journals are spreading misinformation that harms the American people and suppressing alternative viewpoints.
I study how the norms and institutions of science facilitate discovery and self-correction.
Here's my lightning talk about AI at #acrl2025 this morning. Thanks to @nicoloff.bsky.social for recording.
youtu.be/H2UdS1MqH8w?...
In classes where AI is an info lit instruction component, I cover ethics, but focus on pragmatic issues, e.g., databases and search engines are better tools for finding credible sources that you can assess for authority, saving you work & time. It undercuts overall assumptions about AI and ease.
Could only attend virtually this year, but really enjoying how Ruha Benjamin is complicating what appears to be a lot of "let's throw AI at it" content scheduled for the next few days of the conference. #ACRL2025
Even chatbots get the blues. According to a new study, OpenAI’s artificial intelligence tool ChatGPT shows signs of anxiety when its users share “traumatic narratives” about crime, war or car accidents. And when chatbots get stressed out, they are less likely to be useful in therapeutic settings with people. The bot’s anxiety levels can be brought down, however, with the same mindfulness exercises that have been shown to work on humans.
You have to be kidding me.
www.nytimes.com/2025/03/17/s...
Would love a follow up that evaluates sourcing on more typical user queries! Anecdotally, your findings square roughly with what I've noticed about sourcing for more standard information seeking-type prompts, but 'find this exact quote' is pretty distinct from 'answer this and provide support'.
Although this study would suggest that you might have a difficult time verifying the output for that prompt, because the sourcing may be incorrect, incomplete, or misleading. And if you're not an expert on drugs or genetics, you definitely shouldn't trust the output without verification.
That phrasing got me at first, too, but the queries in the study were "here's a quote, find me the source," so it mostly just establishes that sourcing is garbage. This is a very big deal, but shouldn't be extrapolated out to reliability of all output.
I had such a good time doing this. Thanks to @alexhanna.bsky.social and @emilymbender.bsky.social for inviting me on!
Definitely worrying that an expert in assessment and digital learning is so overwhelmed with the narrative around AI as an efficiency engine that he steps right past a well-established, more reliable solution.
"Referencing—citing sources—may be a good example of something that can be offloaded to AI, he said. . . ."
Good example of why you always start with the problem you're trying to solve and don't go in search of problems for a predetermined solution. Citation managers already do this very well.
Excellent list! Would also recommend The Thin Man (1934) for both Christmas adjacency and William Powell-Myrna Loy chemistry.
Can you say more about 'you want to know what some objections to an idea might be?' I'd think that to judge whether an objection to an idea is credible (rather than just possible), you need a source to evaluate, meaning this info need, too, would benefit much more from search than generative AI.
3. Making searching and info lit best practices resonate with people isn't easy even in an academic environment where librarians can actually teach the stuff. People take cues from the tools, and if the tools encourage sloppy use, any counter programming is at a huge disadvantage. /end