Rendering Research on Algorithmic Image Systems
Keywords:collective indexing, network, scale, algorithmic image, database aesthetics, distributed curating
Image has gone hyper, can research catch up? This essay proposes collective indexing as an alternative to academic publishing for rendering research on fast-changing and larger-than-human subjects such as algorithmic images. Following the introduction of notions of network and scale in my research, the essay articulates the value of collective indexing while mapping out contemporary examples. Collective indexing produces new ways of knowledge making and community building, as well as new forms of research aesthetics apt for addressing the distributed nature of algorithmic image systems.
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