Can the algorithm become physical? Fabiola Larios shows us how our digital self-representations can inform a greater understanding of the anthropology of social media.
Fabiola Larios (b. 1986, Mexico) is an interdisciplinary Mexican artist. Her work tackles questions about identity, vulnerability, and the presentation of the self online. Through the use of machine training and information and image extraction, Larios asks us how we declare and maintain autonomy over our internet personas in order to bring attention to the seemingly daunting control the internet has over-representation. Through her work, she plays with the dystopia of machine learning and the effects it has on the way people are perceived in real life. In doing so, Larios alters reality and presents fantastical images, poking fun at the selfie and digital avatar. Her medium allows her to suspend facial recognition and manipulate it, reinforcing value in the imaginary, while challenging social media’s portrayal of its users.
I’m interested in the current techno-political environment surrounding data sensitivity and surveillance capitalism, through the historical context of appropriation in contemporary art. The issues of data sensitivity and privacy in regards to machine learning, how we treat our information with such little care that it is easily available to be used for profit, advertising campaigns, and against us at our expense. Accessible data on the internet is now public property for computational and economic gains.