IDEAS home Printed from https://ideas.repec.org/a/pal/develp/v62y2019i1d10.1057_s41301-019-00207-2.html
   My bibliography  Save this article

Labour, Justice and the Mechanization of Interpretation

Author

Listed:
  • Larry Lohmann

    (The Corner House)

Abstract

The biggest frontier of mechanization of the past 10 years has been the automation, broadly speaking, of interpretation. This includes recognition (for example, image recognition technologies used by security services), translation (Google Translate), searching for information (search engines), understanding (‘predictive algorithms’ that learn what books or movies you will like or what kind of propaganda will appeal to you, as used by Amazon, Netflix, or the Donald Trump campaign), trust (blockchain technologies such as Bitcoin), and negotiation (‘smart contracts’ as pioneered by firms such as Ethereum). This article explores how these technologies benefit business and why they have come to prominence now, the ways they degrade and exhaust the work of both humans and nonhumans, the parallels with earlier uses of machines to discipline and extract value from labour, and the implications for social movement strategy. The article also suggests some directions for research.

Suggested Citation

  • Larry Lohmann, 2019. "Labour, Justice and the Mechanization of Interpretation," Development, Palgrave Macmillan;Society for International Deveopment, vol. 62(1), pages 43-52, December.
  • Handle: RePEc:pal:develp:v:62:y:2019:i:1:d:10.1057_s41301-019-00207-2
    DOI: 10.1057/s41301-019-00207-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41301-019-00207-2
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41301-019-00207-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:develp:v:62:y:2019:i:1:d:10.1057_s41301-019-00207-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.