Many academic disciplines use data science to analyze contemporary culture. The question posed by Lev Manovich in this lecture is: shall we continue to aggregate big cultural data and reduce it to a small set of patterns? Or shall we refuse this dominant paradigm instead and focus on diversity, variability and differences (including tiny ones), i.e., work on big cultural data without aggregation and with attention to what is infrequent and outliers?
Dr. Lev Manovich is a Professor of Computer Science at The Graduate Center, CUNY, and a Director of the Cultural Analytics Lab that pioneered analysis of visual culture using computational methods. Manovich is the author and editor of 13 books including “AI Aesthetics”, “Theories of Software Culture”, “Instagram and Contemporary Image”, “Software Takes Command”, “Soft Cinema: Navigating the Database” and “The Language of New Media” which was described as “the most suggestive and broad ranging media history since Marshall McLuhan”.