Imagining the Thinking Machine_author draft.pdf (183.25 kB)
Imagining the thinking machine: Technological myths and the rise of artificial intelligence
journal contribution
posted on 2017-06-02, 08:45 authored by Simone NataleSimone Natale, Andrea BallatoreThis article discusses the role of technological myths in the development of Artificial Intelligence (AI) technologies from 1950s to the early 1970s. It shows how the rise of AI was accompanied by the construction of a powerful cultural myth: the creation of a thinking machine, which would be able to perfectly simulate the cognitive faculties of the human mind. Based on a content analysis of articles on Artificial Intelligence published
in two magazines, the Scientific American and the New Scientist, which were aimed at a broad readership of scientists, engineers, and technologists, three dominant patterns in the construction of the AI myth are identified: (1) the recurrence of analogies and discursive shifts, by which ideas and concepts from other fields were employed to describe the functioning of AI technologies; (2) a rhetorical use of the future, imagining that present shortcomings and limitations will shortly be overcome; (3) the relevance of controversies around the claims of AI, which we argue should be considered as an integral part of the discourse surrounding the AI myth.
History
School
- Social Sciences
Department
- Communication, Media, Social and Policy Studies
Published in
ConvergenceVolume
26Issue
1Pages
3 - 18Citation
NATALE, S. and BALLATORE, A., 2017. Imagining the thinking machine: Technological myths and the rise of artificial intelligence. Convergence, 26 (1), pp.3-18.Publisher
SAGE © The Author(s)Version
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Acceptance date
2017-05-23Publication date
2017-06-20Notes
This paper was accepted for publication in the journal Convergence and the definitive published version is available at https://doi.org/10.1177/1354856517715164.ISSN
1354-8565eISSN
1748-7382Publisher version
Language
- en