IDEAS home Printed from https://ideas.repec.org/a/spr/minsoc/v24y2025i2d10.1007_s11299-025-00320-5.html
   My bibliography  Save this article

Don’t judge a film by its thumbnail: the question of cybernetic intentionality

Author

Listed:
  • Kristina Šekrst

    (University of Zagreb)

Abstract

This paper examines Netflix’s use of personalized thumbnails, framing the discussion within cybernetic and psychological contexts to explore the nature of intentionality in automated systems. While algorithms are designed to optimize user engagement, the ascription of “intentionality” to such systems requires careful delineation between human and machine agency. By analyzing the processes underlying automated personalization, this paper situates algorithmic behavior within a cybernetic framework, showing that while algorithmic ‘intentionality’ arises from emergent processes, it remains functionally distinct from moral agency. The discussion contributes to the broader debate on the ethical implications of algorithmic design and communication strategies.

Suggested Citation

  • Kristina Šekrst, 2025. "Don’t judge a film by its thumbnail: the question of cybernetic intentionality," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 24(2), pages 1047-1059, December.
    • Handle: RePEc:spr:minsoc:v:24:y:2025:i:2:d:10.1007_s11299-025-00320-5
    DOI: 10.1007/s11299-025-00320-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11299-025-00320-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11299-025-00320-5?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:spr:minsoc:v:24:y:2025:i:2:d:10.1007_s11299-025-00320-5. 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.springer.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.