TY - JOUR
T1 - The Living Machine
T2 - A Computational Approach to the Nineteenth-Century Language of Technology
AU - Wilson, Daniel
AU - Beelen, Kaspar
AU - Coll Ardanuy, Mariona
AU - McGillivray, Barbara
AU - Ahnert, Ruth
N1 - Funding Information:
The authors are grateful to the reviewers, to Jon Lawrence and Emma Griffin, and the Living with Machines team. This project, funded by the UK Research and Innovation (UKRI) Strategic Priority Fund, is a multidisciplinary collaboration delivered by the Arts and Humanities Research Council (AHRC grant AH/S01179X/1) with The Alan Turing Institute, the British Library, and the Universities of Cambridge, East Anglia, Exeter, and Queen Mary University of London.
Publisher Copyright:
© 2023 by the Society for the History of Technology. All rights reserved.
PY - 2023/8/11
Y1 - 2023/8/11
N2 - This article examines a long-standing question in the history of technology concerning the trope of the living machine. The authors do this by using a cutting-edge computational method, which they apply to large collections of digitized texts. In particular, they demonstrate the affordances of a neural language model for historical research. In a deliberate maneuver, the authors use a type of model, often portrayed as sentient today, to detect figures of speech in nineteenth-century texts that portrayed machines as self-acting, automatic, or alive. Their masked language model detects unusual or surprising turns of phrase, which could not be discovered using simple keyword search. The authors collect and close read such sentences to explore how figurative language produced a context that conceived humans and machines as interchangeable in complicated ways. They conclude that, used judiciously, language models have the potential to open up new avenues of historical research.
AB - This article examines a long-standing question in the history of technology concerning the trope of the living machine. The authors do this by using a cutting-edge computational method, which they apply to large collections of digitized texts. In particular, they demonstrate the affordances of a neural language model for historical research. In a deliberate maneuver, the authors use a type of model, often portrayed as sentient today, to detect figures of speech in nineteenth-century texts that portrayed machines as self-acting, automatic, or alive. Their masked language model detects unusual or surprising turns of phrase, which could not be discovered using simple keyword search. The authors collect and close read such sentences to explore how figurative language produced a context that conceived humans and machines as interchangeable in complicated ways. They conclude that, used judiciously, language models have the potential to open up new avenues of historical research.
UR - http://www.scopus.com/inward/record.url?scp=85167984978&partnerID=8YFLogxK
U2 - 10.1353/tech.2023.a903976
DO - 10.1353/tech.2023.a903976
M3 - Article
SN - 0040-165X
VL - 64
SP - 875
EP - 902
JO - TECHNOLOGY AND CULTURE
JF - TECHNOLOGY AND CULTURE
IS - 3
ER -