Sandy Hervieux

This is an edited volume with the theme of artificial intelligence in libraries. It's come out right when hype around artificial intelligence is at a peak, and when most of the references to artificial intelligence are about machine learning.

At first, I was a little sad that most of these chapters are little things, like do a workshop about machine learning, instead of large scale metadata projects. Actually, nothing covered in this book is large scale. It's all tiny little things presented as case studies, with a few chapters that are abstract and try to overview some aspect of artificial intelligence. I came eventually to think of this as a strength. Most things in this book are achievable almost anywhere, because the projects presented as case studies are small scale and tend to have event programming as the big lift rather than technology as the big lift. The chapters here are mostly case studies about little teeny things in libraries, so it is something that if you work in a library, you can read the abstract for each chapter and probably find something that is achievable at your library. When I approached it like this, I found two things that could be incorporated into what the libraries I work at are already doing, and I snapped a photo of those pages, so I can reference them later.

Meanwhile... When I have looked at big artificial intelligence projects, many are long term, are more structured than you think, and are controlled by vendors. I do wish libraries controlled the technology in so many areas, including just storing PDFs for decades on our own servers to allow access, but here we are.… (altro)