In Deep Belief, I am setting out to recontextualize the semiotics and human interactions of a world that we have grown all too comfortable with by introducing the computer as a machine that knows us better than we know ourselves. I am attempting this by abandoning our contemporary logic of raw data, and instead using generative algorithms as a framework for viewing the human condition. Deep Belief addresses this dialectic of agency because if it's left unexplored, then we reject the various new windows of creativity, philosophy, and metaphysics that the computer could potentially offer us.
Deep Belief takes form in both print and digital form with the inclusion of mockups, posters, an animation, and a book to bring these ideas back into physical space. The 5 symbols that I have worked with throughout the span of my project represent the 5 most common modes of human interaction: competition, exchange, conflict, cooperation, and accommodation. These symbols are used in a way that replaces the written word so that we are forced to familiarize ourselves with how our master controls view the politics of our intimacies. Once a basic understanding of these symbols is acquired by the viewer, my work also envisions hybrid interactions by drawing new connections between each symbol. Also, I experiment with a natural language processing technique called Markov Chain that builds text based off of a computer’s understanding of a book on social psychology and is used because this process matches the generative style of my symbol making.