Techno-Schizo is an interactive AI performance in which the artist examines her own visibility through the lens of an AI facial recognition system. The system is an off-the-shelf pre-trained software which recognizes faces and analyzes features based on external appearance. These features include gender, race, age and emotion classifications along with facial features and accessories such as type of hair, size of nose and lips, hair style, facial hair, eyewear, makeup and more. By utilizing a performative behavior the artist changes her facial expressions and her hair style in order to modify the confidence level by which the machine analyzes her appearance.
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Scholar Paul Preciado claims that if machine vision algorithms can guess facets of our identity based on our external appearance, it is not because these facets are natural features to be read, it is simply because we are teaching our machines the language of techno-patriarchal binarism and racism.
Face recognition algorithms are becoming increasingly prevalent in our environment. They are embedded in products and services we use on a daily basis. Recent studies demonstrate that many of these algorithms reflect social disparities and biases which may harshly impact people’s lives. This is especially true for people from underrepresented groups. However, it is important to remember that these systems are not ‘things-of-themselves’; there is no reason for them to be outside of our reach. We are able to intermingle with these systems so that we better understand the coupling between the information and our own bodies. This entanglement, as seen in the performance, reveals our own agency and ability to act.
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As AI systems continue to develop, it is crucial to ask questions regarding their impact on our society as a whole and on our individual behavior. Will we let these systems see us as they are programmed to see us? or will we be forced to perform our identity so that we make them see us as we wish to be seen?
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