Currently on organizing committee of FORCE2026, Singapore, 3-5 June 2026.
I'm librarian + blogger from Singapore Management University. Social media, bibliometrics, analytics, academic discovery tech.
Aaron Tay
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To be clear, I'm not saying you need to be a AI scientist or anything but there are many levels of expertise/knowledge between that of a typical librarian and that of a "AI scientist". Often people act like it's one or other...
"Librarians already have all the skills we need for AI/search/the future. We just need confidence." Can we stop with BS like this? It's just embarrassing.
And it's not the AI thing either. I've been in the profession long enough to see such sentiments emerge to any new challenge. All but saying "We are good enough, don't have to learn anything else"
Ironic given librarians support of. learning. Worse it's often paired with "only we can save the day"
And someone's going to complain to me that librarians are way too busy and overworked to learn new things. Sure, even if that's true for some, then don't expect to be taken seriously when talking about such subjects
Slight complement to my horseless carriage argument. I argued LLM generating boolean is not useful except in rare cases where you can get zero hits, this isn't the case in most article search. But this is common when trying to find the right dataset/non-article database e.g. econ/finance databases!
[Blogged] What a year of testing & thinking about AI academic search taught me aarontay.substack.com/p/what-a-yea...
