🧵 A first passage problematizes the naturalization of biological computation as sociotechnical digitization, which has turned neurons into artificial neurons (life or thought itself is always universal, as shown by the continuing orientation toward the human brain—which brain research itself does not follow lightly—on the supposed path to general artificial intelligence). /1
🧵 A second passage addresses the enduring neo-cybernetic impulse that leads to the emergence and recurrence of cognitivist and behaviorist connectionism (as with cybernetics itself, this primarily affects the human sciences, including cognitive science, psychology, statistics, economics, anthropology, Bildwissenschaft, and linguistics). /2
🧵 A third passage traces the enormous amount of public research funding (20th century) and private investment (21st century) that is used to finance AI (thus making “follow the money” a methodological imperative). /3
🧵 A fourth passage resulting from this takes into account connectionist formations of practices, media, and data that contribute to the practical generalization of (initially mostly specialized) AI applications in certain constellations—and in others rather not. /4
🧵 A fifth passage theorizes the plural practices of testing that make AI publicly available, i.e., marketable, and at the same time habitualize its use. /5
🧵 A sixth passage reveals neocolonial data economies and geopolitics that extract, automate, and industrialize human semiotic resources and—crucially for the future of media and cultural studies— /6
🧵 The seventh passage considers the transformation of all media through their digitization as statistical/stochastical AI. /7
🧵 For to the extent that the analysis and generation of language, texts, numbers, images, and sounds is based on layers of neural networks, all media—including film and computer code—potentially become statistically operationalized, stochastically-driven data-intensive networks. /end