AI glasses, spatial interfaces, and the library-shaped operating layer for inquiry In my last post, I noted some of my early thoughts around what I described as the closed-book effect: the way a fluent and seamless AI response can make learning feel finished before the researcher has even opened the sources. The problem was not only that AI might be wrong. The problem was that AI might feel complete. I have been trying to imagine what comes after that. Because the dominant AI

AI, the illusion of completion, and what librarians might build after chatbots A student types a research question into an AI tool. The answer appears quickly. It has a calm tone. It has sections. It uses the right vocabulary. It may even include citations. It does not look messy or unfinished, which is exactly the problem. Before the student has searched a database, compared sources, checked a citation, opened an article, noticed a gap, or changed their mind, the work alrea

If you work in libraries or archives long enough, someone eventually sends you a PDF that looks perfectly normal in a viewer, but refuses to cooperate. You cannot search it, you cannot copy text, and any attempt to extract content gives you nothing useful. This happened to me with a conference program and abstract booklet that a researcher needed to search and mine for content. The PDF looked crisp. The fonts were clean. It behaved like a real document in every way except the

I'm working on a Python project involving scientific publishing data. In the pursuit of enhancing medical knowledge accessibility through data science, I've utilized an emerging AI research tool known as Elicit, Python's Pandas library to analyze trends in epilepsy surgery publications. We'll analyze trends, popular research topics, and changes in scientific thought over time and perform basic data analysis on a scientific publishing dataset. This will include loading the dat