Aesthetics of Uncertainty

Machine learning has a tendency to reveal inconsistencies which have transversal relevance bridging computer science with art and the humanities. Rather than purely situations of inconsistency, discrepancy, or malfunction, Derrida’s notion of aporia describes uncertainty as a precondition of dialectics. Expanding on Derrida’s line of thinking, this paper speculates that the internal frictions which can be found in artificial intelligence and machine learning systems may be understood in terms of a new kind of aesthetic informed by uncertainty.