Anomaly can only be detected against the ground of pattern regularity. Media theorist Matteo Pasquinelli explores the return of the abnormal into politics as a mathematical object.

The Mathematization of the Abnormal in the Metadata Society

In this essay, media theorist Matteo Pasquinelli reflects on the return of the abnormal into politics as a mathematical object. Algorithmic vision is about the understanding of vast amounts of data according to a specific vector: it may be about common patterns of behavior in social media, suspicious keywords in surveillance networks, buying and selling tendencies in stock markets, or the oscillation of temperature in a specific region of the planet. The eye of the algorithm blindly records emerging properties and forecasts tendencies based on large data sets. Such procedures of computation are pretty repetitive and robotic and they generally operate along two main functions: pattern recognition and anomaly detection. The two epistemic poles of pattern and anomaly are two sides of the same coin of algorithmic governance. An unexpected anomaly can be detected only against the background of pattern regularity. And, conversely, a pattern emerges only through the median equalization of different tendencies. Here, mathematics resounds immediately as a new epistemology of power.