Algorithms of vision: Human and machine learning in computational visual culture

PhD research by Nicolas MalevĂ© (collaborative PhD with The Photographers’ Gallery)

Today, as we are confronted on a daily basis with millions of images on the Internet, grasping the visual world seems an overwhelming task. My research asks how we now make sense of images in a context where algorithmic techniques proliferate and produce nonhuman understanding of the world as perceived through vision. What is at stake here is not only a huge increase of the quantity of images but a new articulation of the relations between vision, information and knowledge.

As Computer Vision algorithms and descriptive data are combined to organize and classify large image collections, my research will revolve around the following questions:

How do we understand collections of photographs through the relations between algorithmic techniques and training data? What kind of regime of visibility is established for the digital image by discriminatory algorithms? What are the epistemological questions produced through a nonhuman understanding of the visual field? What new forms of visual literacy are required? What consequences have the curatorial dimension of machine classification for the development of curatorial practices in the field of contemporary photography?