by Matteo Pasquinelli
Canonical example of apophenia: a ‘human face’ recognized on the surface of Mars (photo: NASA, 25 July 25, 1976, Wikipedia Commons)
In a book from 1890 the French sociologist and criminologist Gabriel Tarde was already recording the rise of information surplus and envisioning a bright future for the discipline of statistics as the new eye of mass media (that is as a new computational or algorithmic eye,we would say today). In his biomorphic metaphors, he wrote:
The public journals will become socially what our sense organs are vitally. Every printingoffice will become a mere central station for different bureaus of statistics just as the ear-drumis a bundle of acoustic nerves, or as the retina is a bundle of special nerves each of whichregisters its characteristic impression on the brain. At present Statistics is a kind of embryoniceye, like that of the lower animals which see just enough to recognise the approach of foe orprey.¹
This quote can help to introduced four fields of discussion that are crucial in the age of algorithms. First, as the reference to enemy recognition suggests the realm of battle fields and warfare, military affairs and geopolitics (and therefore of forensics, as counter-practice). Second, as this reference brings us to the field of sociology and criminology, to the definition and institution of the ‘internal enemy’ of society (that is the abnormal in the tradition of Foucault and Canguilhem). Third, we see clearly an enemy also from the point of view of labour exploitation, according to which the worker is an anomaly to measure, optimise and often criminalise (as Marxism would records). Forth, we could envision an autonomous agency for the supercomputers of statistics as in the idea of General Artificial Intelligence and the nightmares of so-called Singularity, where it is this very alien scale of computation to become inimical to the human (see the recent neorationalist/accelerationist debate). In these cases, of course, the position of the enemy, of the anti-social individual as much as of the reluctant worker that falls under the eye of statistics and algorithms for data analysis, can be reversed and a new political subject can be described and reconfigured, as the research project Forensic Architecture has recently stressed.²
A further evolution of that primitive eye described by Tarde, today’s algorithmic vision is about the understanding of global data sets according to a specific vector. The eye of the algorithm records common patterns of behaviours in social media, suspicious key words in surveillance networks, buying and selling tendencies in stock markets or the oscillation of temperature in a specific region. These procedures of mass computation are pretty universal,repetitive and robotic, nevertheless they inaugurate a new scale of epistemic complexity(computational reason, artificial intelligence, limits of computation, etc.) that will not bead dressed here. From the theoretical point of view, I will underline only the birth of a new³ epistemic space inaugurated by algorithms and the new form of augmented perception and cognition: what is called here ‘algorithmic vision’. More empirically, the basic concepts and functions of algorithmic vision and therefore of algorithmic governance that I will try to explain are:
pattern recognition and anomaly detection. The two epistemic poles of pattern and anomaly are the two sides of the same coin of algorithmic governance. An unexpected anomaly can be detected only against the ground of a pattern regularity. Conversely, a pattern emerges only through the median equalisation of diverse tendencies. In this way I attempt to clarify the nature of algorithmic governance and the return of the issue of the abnormal under a mathematical fashion.
¹Gabriel Tarde, The Laws of Imitation, New York: Holt, 1903 [first published in French in 1890], p.136.
²See: Forensic Architecture (ed.), Forensis: The Architecture of Public Truth, Berlin: Sternberg Press, 2014. And also: www.forensic-architecture.org
³For a treatment of these issues see: Luciana Parisi, Contagious Architecture: Computation, Aesthetics, and Space, Cambridge, MA: MIT Press, 2013.