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The 2020s political economy of machine translation

Published online by Cambridge University Press:  10 December 2021

Steven Weber Open the ORCID record for Steven Weber [Opens in a new window]  and
Nikita Mehandru
Steven Weber*
Affiliation:
University of California Berkeley, School of Information, Berkeley, CA 94720, USA.
Nikita Mehandru
Affiliation:
University of California Berkeley, School of Information, Berkeley, CA 94720, USA.
*
*Corresponding author: Steven Weber, email: steve_weber@berkeley.edu
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Abstract

This article specifies and explores the hypothesis that the diversity of human languages, right now a barrier to “interoperability” in communication and trade, will become significantly less of a barrier as machine translation technologies are deployed over the next several years. We argue that machine translation will become the 2020's analogy for ideas, to what container shipping did for goods trade in the second half of the twentieth century. But as with container shipping or railroads in the nineteenth century, this new boundary-cost and transaction-cost reducing technology does not reduce all boundary and transaction costs equally, and so creates new challenges for the distribution of ideas and thus for innovation and economic growth. How we develop, license, commercialize, and deploy machine translation will be a critical determinant of its impact on trade, political coalitions, diversity of thought and culture, and the distribution of wealth.

Keywords

tradeglobalizationmachine translationinequalityproductivity
Type
Research Article
Information
Business and Politics , Volume 24 , Issue 1 , March 2022 , pp. 96 - 112
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of V.K. Aggarwal

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Footnotes

This work was supported in part by the Hewlett Foundation under a grant to the Center for Long Term Cybersecurity at Berkeley and by the Berggruen Institute (Los Angeles) where the author is a Berggruen Fellow.

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