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THE INTUITIVE AND THE COUNTER-INTUITIVE: AI AND THE AFFECTIVE IDEOLOGIES OF COMMON SENSE.

Authors :
Pedwell, Carolyn
Source :
New Formations. 2024, Issue 112, p70-93. 24p.
Publication Year :
2024

Abstract

Animating the relationship between affect and ideology in histories of artificial intelligence, this paper explores how the transatlantic post-war quest to engineer common sense via computational means has profoundly shaped both the social logics of machine learning systems and the sensorial politics of everyday knowledge production. Focusing on the Cyc project, a logic-based AI endeavour to 'codify human common sense' which began at the USA-based Microelectronics and Computer Technology Corporation in 1984, and making links to MIT Media Lab's Open Mind Common Sense Project inaugurated in 1999, I trace how the imperative within late twentieth-century computer science to make intelligent systems more intuitive by translating implicit human knowledge into explicit machine knowledge involved not only mathematical and technological challenges but also affective, ideological and socio-political ones. In tracking the interactions between intuition and common sense across these genealogies of machine intelligence, I tease out some of the key atmospheres, processes, and correlations via which AI technologies have become embedded with ideology, normativity and prejudice at the levels of logic, procedure and data. Through adjudicating the meanings of reason, truth and perceptibility as matters of algorithmically calibrated fit and popularity, intelligent architectures are also radically reconstituting the intelligible and the sensible - in ways, I argue, that complicate any notion of a clean epistemological or ontological break between first and second wave AI. Dwelling within these unfinished histories, however, also points to how inhabiting counter-intuitive tendencies may open up new possibilities for (un)common sense and distributed intuition within computational cultures. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09502378
Issue :
112
Database :
Academic Search Index
Journal :
New Formations
Publication Type :
Academic Journal
Accession number :
180714118
Full Text :
https://doi.org/10.3898/NewF:112.04.2024