The Epistemology of Code in the Age of Machine Learning

Code is an epistemic system predicated on the repression of state, but with the rise of global optimization and machine learning algorithms, code functions just as much to obscure knowledge as to reveal it. Code is constructed in response to two characteristics of the twentieth century episteme. First, knowledge is represented as a process. Second, this representation must be sufficient, such that its meaning is constituted by the representational form itself. In attempting to meet these requirements, process is separated into an essential part, code, and an inessential part, state. Although code has a relationship with state, in order to construct code as an epistemic object, state is limited and suppressed. This construction begins with the first formation of code in the 1940s and reaches its modern form in the structured programming movement of the later 1960s. But now, with the increasing dominance of global optimization and machine learning algorithms in computing, it has become apparent that state is vitally important, and yet our tools for understanding state are inadequate. This epistemic inadequacy nevertheless serves those who would act dangerously and shun responsibility for the consequences.