On June 22nd, digital culture theorist Lev Manovich gave an online talk entitled, “What Does Data Want? Can We Think Without Categories? Can Computer Vision Help Us Understand Art?” The talk is now available to view via YouTube.
In the last fifteen years, many researchers started to apply AI and data science methods to the analysis of large cultural datasets. This research generated many interesting results, leading to hundreds of thousands of conference papers and journal articles, and development of new research areas and paradigms (a big part of digital humanities, cultural analytics, culturomics, etc.)
But is it possible that we remain blind to the fundamental differences between cultural data and other kinds of data? Why do we approach cultural and social data today using ideas developed in the 18th and 19th century, before digital computers and big data? How do aesthetic experiences made possible by millions of Instagram images by non-professional creators challenge computer vision?