Abstract
Filters – both technically and in a wider sense of the term – provide a new way of theorizing photography. Most obviously, filters sieve things, persons and data out of flows; more specifically, they are key to the non-optical formations at work in image production based on neural networks in machine learning. In this essay, we argue that theorizing photography from the perspective of filtering reconfigures photography as the entire field of material elements and processes involved in the production of an image and presents the photographic image itself as a distribution across a field of perception that includes various forms of technical sensing and formation. Ultimately, attending to filtering as the technical realities as well as aesthetic propositions in recent art projects allows us to understand photographic conditions as a wider and more general set of environments in which image-events occur with many kinds of causality and manifestation.
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