How are museums using artificial intelligence, and is AI the future of museums? It was interesting to see all the uses of AI. Some were more utilitarian (predicting visitor turn out), and some were more for visitor engagement (Pepper, for example). There were a few projects mentioned that I didn’t fully understand the end goal. One was the first project mentioned: Berenson. Perhaps this robot informs the museum staff of the visitor reactions, so they have a sense of how their exhibits were received. But then why does it need to be a robot that rolls around the museum floor? Why not a series of cameras throughout the space? A second that I didn’t see the larger picture was Google’s Art Selfie. This seemed to mostly be an exercise in facial recognition (and maybe data collection) than something that would help people engage with art deeper.

If these projects are steps to a larger impact, that makes sense. I just hope that museums don’t stop here, and they use the learnings from these projects to continue integrating AI into their experiences.

The Shape of Art History in the Eyes of the Machine I’m curious how the authors were able to “label” the axes. Perhaps I haven’t seen enough papers like this, but I was under the impression that there was no way to know why an AI algorithm performed the way it does. Yet, the artists say one axis, for example, “seems to correlate with figurative art” or “correlates with the linear versus painterly.” This meant art historians assessed the results to give these labels, right? How does that impact the results?

I can see a lot of uses for this algorithm. In particular, I wonder how this network can be used to categorize art that is missing its context (date, artist, region). Early on in the semester, someone noted that one museum is revisiting a number of the works and finding that they were painted by women, and maybe sold as her brother’s work. If a women and man collaborated on a collection, could this algorithm help sort out which paintings are hers and which are his?