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There's No Data Like More Data

Automatic Speech Recognition and the Making of Algorithmic Culture

Bibliographic Data

ID3924475
AuthorsXiaochang Li (0000-0002-6203-7197, corresponding author)
Year2023
Volume38
Pages165-182
Publication date2023-07-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueOsiris (JOURNAL)
Journal identifiersISSN: 0369-7827 • E-ISSN: 1933-8287
PublisherUniversity of Chicago Press (PUBLISHER • US)
DOI10.1086/725132
OpenAlexW4383744282
LanguageEN
Citations received9
References cited32

This article examines the role of automatic speech recognition research in the rise of data-driven machine learning as a privileged and pervasive form of computational knowledge. It focuses on IBM’s Continuous Speech Recognition group between 1972 and 1993 as they fueled speech recognition’s “statistical turn,” uprooting the field from the simulation of human reason and language understanding and redirecting it toward the acquisition of data for large-scale pattern recognition. This shift, I argue, was instrumental in the remaking of artificial intelligence and computational modeling into radically data-centric pursuits that underpin algorithmic culture today. In doing so, this history offers a critical piece in the story of how we became data-driven, highlighting how efforts to turn language into data consequently turned data into an imperative, preparing the way for the widespread incursion of algorithmic authority across everyday life

Cognitive science · Data science · Epistemology · Everyday life · IBM · Computer Science · Cybernetics and Technology in Society · History of Computing Technologies · Information Systems Theories and Implementation · Psychology · Artificial Intelligence

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Unique citing works9
Citations per year3
Citation span2023 - 2026 (4)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 9

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