On Thursday, March 31 (5pm Central US time), I’ll be participating along with Jihoon Kim, John Powers, and Deborah Levitt in a panel titled “(Post)Cinematic Operations: Envisioning Cameras from the Bolex to Smart Sensors” at this year’s (virtual) SCMS conference.
My paper is titled “AI, Deep Learning, and the Aesthetic Education of the ‘Smart’ Camera.” Here’s the abstract:
The merging of “smart” technologies with imaging technologies creates a number of conceptual difficulties for the definition of the word camera. It also creates a number of aesthetic and phenomenological problems for human sensation. As I argued in my book Discorrelated Images, the microtemporal speed of computational processing inserts itself in between the production and reception of images and endows the camera with an affective density that distinguishes it from a purely mechanical reproduction of visible forms; in processes like motion prediction and motion smoothing, the distinction between camera and screen itself breaks down as images are generated on the fly during playback. This presentation takes these considerations further to think about the ways that artificial intelligence further transforms inherited forms and functions of camera-mediation, both in physical apparatuses (e.g. smartphones and drones) and virtual ones (e.g. software-based image generation in videogames, DeepFake videos, AR, or VR). The analysis proceeds by looking at concrete instances such as the “Deep Fusion” technique employed on recent iPhones, which use the A15 Bionic processor—a so-called “neural engine”—to create a composite image combining pixels from a quick burst of digital photos. Beyond merely technical advances, I argue, such “smart” camera processes effect a subtle but significant transformation of our own aesthetic senses, insinuating computational processes in both our low-level processing of sensation and our high-level aesthetic judgments (and thus also algorithmically inserting racial and gendered biases, among other things). A techno-phenomenological analysis, which attends both to technological factors and to the embodied spatiotemporal parameters of human perception, provides the basis for a robustly cultural understanding the “smart” camera, including its role in “re-educating” our aesthetic senses.