The notion and methodology of Lev Manovich’s cultural analytics addresses the problem that digital image media brought about in the last decades: the impossibility to view all or at least a significant fraction of all of the images that circulate in the net. By creating visualizations and thus even more images out of the flood of imagery, complexity is reduced by an enormous amount: we are relieved from viewing any of them any more. Images become data, image datafication takes place even on images that are originally made, thus are facts, not data: fecit, non datur.
All this is made possible by the use of computers, by extracting positive facts from analogue imagery like chrominance, size, creation date, information, redundancy, or whatever is at hand. The similarity to the efforts information aesthetics made is obvious: analyzing and generating images by algorithms. We gain insights beyond taste, we observe with the most modern instruments, we inform ourselves by order, complexity, redundancy and entropy.
What could we learn from information aesthetics, an enterprise that did an epic fail in the end? What could Max Bense’s mathematical philosophy of the objective tell us about the objective reign of information and algorithms of nowadays? Are there promising bridges between the scrawny vector graphics of the sixties and seventies to the exuberant image aggregates after the iconic turn? And: how could connections look like between methods of distant readings of abundant piles of pictures with very close investigations of their details? What, in the end, would be a simulation of the art historian’s gaze by the means of digital computers? Could art history become a branch of computer science? Will aesthetics become big data?