The Nooscope manifested: AI as instrument of knowledge extractivism
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ORIGINAL ARTICLE
The Nooscope manifested: AI as instrument of knowledge extractivism Matteo Pasquinelli1 · Vladan Joler2 Received: 27 March 2020 / Accepted: 14 October 2020 © The Author(s) 2020
Abstract Some enlightenment regarding the project to mechanise reason. The assembly line of machine learning: data, algorithm, model. The training dataset: the social origins of machine intelligence. The history of AI as the automation of perception. The learning algorithm: compressing the world into a statistical model. All models are wrong, but some are useful. World to vector: the society of classification and prediction bots. Faults of a statistical instrument: the undetection of the new. Adversarial intelligence vs. statistical intelligence: labour in the age of AI. Keywords Nooscope · Political economy · Mechanised knowledge · Information compression · Ethical machine learning
1 Some enlightenment regarding the project to mechanise reason The Nooscope is a cartography of the limits of artificial intelligence, intended as a provocation to both computer science and the humanities. Any map is a partial perspective, a way to provoke debate. Similarly, this map is a manifesto—of AI dissidents. Its main purpose is to challenge the mystifications of artificial intelligence. First, as a technical definition of intelligence and, second, as a political form that would be autonomous from society and the human.1 In the expression ‘artificial intelligence’, the adjective ‘artificial’ carries the myth of the technology’s autonomy; it hints to caricatural ‘alien minds’ that self-reproduce in silico but, actually, mystifies two processes of proper alienation; the growing geopolitical autonomy of hi-tech companies and the invisibilization of workers’ autonomy worldwide. The modern project to mechanise human reason has clearly mutated, in the twenty first century, into a corporate regime of knowledge extractivism and epistemic colonialism.2 This is unsurprising, since machine learning algorithms are the most powerful algorithms for information compression. * Matteo Pasquinelli mpasquinelli@hfg‑karlsruhe.de 1
Media Philosophy Department, Karlsruhe University of Arts and Design, Karlsruhe, Germany
New Media Department, Academy of Arts, University of Novi Sad, Novi Sad, Serbia
2
The purpose of the Nooscope map is to secularize AI from the ideological status of ‘intelligent machine’ to one of knowledge instruments. Rather than evoking legends of alien cognition, it is more reasonable to consider machine learning as an instrument of knowledge magnification that helps to perceive features, patterns, and correlations through vast spaces of data beyond human reach. In the history of science and technology, this is no news; it has already been pursued by optical instruments throughout the histories of astronomy and medicine.3 In the tradition of science, machine learning is just a Nooscope, an instrument to see and navigate the space of knowledge (from the Greek skopein ‘to examine, look’ and noos ‘knowledge’). Borrowing the idea
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