- Natasha Matteson
What if exhibition-making consisted simply of a rule set generating a selection of artworks? Criteria is an exhibition of artworks from the Marieluise Hessel Collection that complicates the divide between algorithmic and curatorial decision-making. Though the process of curatorial selection may seem to emerge from the independent interests of the curator, these choices are actually deeply enmeshed with metrics and optimization. On the one hand, logistical factors, from shipping times to budget line distribution, determine which kinds of curatorial projects can be realized. On the other, calibrated search engines and personalized feeds circumscribe our digital windows onto the world—and curatorial research is no exception. Moreover, art writers are pressured by the demands of click-driven media, where algorithms influence both the arts discourse that curators encounter and the way that curatorial endeavors circulate within it. On top of this, even anticipated attendance metrics may determine particular aspects of an exhibition. In some sense, curatorial projects are always optimizing certain metrics, some of which are consciously calculated, and others of which appear natural. Criteria explores those obscured parameters through an investigation of the computational aspects of curating. The public programming developed in conjunction with the exhibition further addresses broad questions around algorithmic bias, artificial intelligence, decision-making, and applications of systems thinking in the museum sphere.
Lead Data Engineer - Nate Turley
Data Visualizer Engineer - Eric Rabinowitz
Data Analysis Engineer - Li-Heng Henry Chang
Assistant Data Engineer - Tsitsi Mambo
Advising Engineer - Sebastian Schloesser
Graphic Designer - Emilio Pérez
Curated in consultation with Marcia Acita, Director of Collections, Center for Curatorial Studies, Bard College
In addition to exhibition support provided by CCS Bard, Criteria was made possible by the Experimental Humanities Collaborative Network and Bard College Computer Science Program’s generous support of the related public programming.