Kurt Ralske’s video installations and performances enact a dialogue with history: an exploration of the past that proposes a new view of the future. His work has been exhibited internationally, including at the Venice Biennale in 2009 and 2015, the Guggenheim Bilbao, and the Los Angeles Museum of Contemporary Art.

Kurt is the recipient of a Rockefeller Foundation Media Arts Fellowship, and received First Prize at the Transmediale International Media Art Festival in Berlin in 2003. Kurt programmed and co-designed the 9-channel video installation that is permanently in the lobby of the MoMA in NYC. He is also the author/programmer of Auvi, a popular video software environment in use by artists in 22 countries.

Kurt resides in New York City. He is Chair of the Department of Media Arts (Film / Animation / Video / Sound / Digital Media) at the School of the Museum of Fine Arts, Boston.

JLG Dataset

Between 1960 and 1967, director Jean‐Luc Godard completed 15 movies, from his classic debut Breathless (1960) to the notoriously extreme Weekend (1967). In JLG Dataset, New York‐based artist Kurt Ralske creates a collision between “big data” analytics and Godard’s universe of poetry and politics. The first 15 films of Godard’s oeuvre are treated as if they are mere information: nothing more than a few hundred gigabytes of pixels or a few megabytes of text — a dataset to be totalized, processed, and analyzed.

In the video JLG Faceness 1960‐1967 (2016), a facial detection algorithm extracts 2 million images of faces from the dataset, which are presented as an ever‐morphing stream of hybridized ghost‐like faces. The complete dialogue from Godard’s films becomes a single monolithic color field (the print Total JLG), or a stream of automatically‐generated text messages (the video JLG on SMS). Statistics created from an analysis of the pixel data of the films are unhelpfully correlated with negative critical reviews dating from the time of the films’ release.

The results thrown up by the analysis of the dataset are mysterious, sublime, oblique, or blank. In the end, the artifacts derived from the “Godard Dataset” do not tell us much about Godard’s films — instead, they point elsewhere, making visible the types of slippage that occur when we attempt to translate information into knowledge.