Thoughts on "Good AI neighbours"
July 2026
Fabian Offert, in his article “Are Nearest Neighbors Good Neighbors?”, talks about similarity as a way to understand how AI models work with images. Offert's main argument is that AI systems cannot look for similarities between artworks in the same way that we do. He uses as an example for comparison throughout his article the Atlas of Aby Warburg (Bilderatlas Mnemosyne), noting how with Warburg's groupings of works of art throughout history, it is sometimes straightforward to identify the similarities (the logic he was using to relate the works), but with some groupings the reasoning is more subtle, requiring some knowledge of the works or the period, or some guessing (so open to interpretation). The key for Offert seems to be that there isn't a clear rule that we can follow to replicate the grouping of images with some new images of our choice.
