IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-676-5_20.html

The Development of a Scale for Recognizing the Human-Machine Subject-Object Relationship in the Philosophical Perspective of Human-Machine Collaboration

In: Proceedings of the 2024 6th Management Science Informatization and Economic Innovation Development Conference (MSIEID 2024)

Author

Listed:
  • Guiqing Li

    (Chengdu University of Information Technology, School of Management)

  • Yanni Lai

    (Chengdu University of Information Technology, School of Management)

  • Jiahao Zhu

    (Chengdu University of Information Technology, School of Management)

Abstract

Based on literature research, this paper develops the scale of human-machine subject-object relationship cognition from the perspective of human-machine cooperation philosophy through focus group interview, expert interview, and questionnaire survey. After exploratory factor analysis and confirmatory factor analysis, it is found that the human-machine subject-object relationship cognition includes three dimensions: deep human-machine cooperation, human-machine superiority complementarity and human intelligence dominance, which has good reliability and validity. It is of great significance to understand the essential attribute, utility goal and ethical value of human-machine relationship after entering the 21st century, and has strong practical reference value.

Suggested Citation

  • Guiqing Li & Yanni Lai & Jiahao Zhu, 2025. "The Development of a Scale for Recognizing the Human-Machine Subject-Object Relationship in the Philosophical Perspective of Human-Machine Collaboration," Advances in Economics, Business and Management Research, in: Manhui Huang & Vilas B. Gaikar & Md Rabiul Islam & Ivan Krumov Todorov (ed.), Proceedings of the 2024 6th Management Science Informatization and Economic Innovation Development Conference (MSIEID 2024), pages 187-198, Springer.
  • Handle: RePEc:spr:advbcp:978-94-6463-676-5_20
    DOI: 10.2991/978-94-6463-676-5_20
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:advbcp:978-94-6463-676-5_20. 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.