IDEAS home Printed from https://ideas.repec.org/h/spr/conchp/978-3-032-13458-5_11.html

Why Is Creative Collaboration With Generative AI Actually Possible? A Theoretical Analysis With Social System Theory and Creative System Theory

In: Artificial Intelligence and Networks for a Sustainable Future

Author

Listed:
  • Takashi Iba

    (Keio University, Faculty of Policy Management)

Abstract

This paper presents a systems-theoretical analysis of creative collaboration between humans and generative AI. Interactive generative AI provides meaningful responses to human inputs and generates ideas, leading many users to perceive it as a “partner” in creative collaboration. How, then, is creative collaboration possible with generative AI despite the absence of consciousness resembling that of humans? To answer this question, this paper examines what is actually occurring from the perspectives of sociologist Niklas Luhmann’s Social Systems Theory and the Creative Systems Theory that I previously proposed. These systems theories conceptualize social communication and creative discovery as autopoietic systems with semantic contexts that operate independently of the human mind. Through these theoretical lenses, it becomes clear that while generative AI systems differ from human psychic systems, they can—through Large Language Models (LLMs) enabling sequential linguistic analysis and generation—serve as the functional equivalent of psychic systems by facilitating the synchronization of meaning within the sequential development of social communication and creative discovery. The paper concludes that the sense that interactions and co-creation with generative AI feel human-like should not be regarded as a mere illusion; rather, generative AI actually functions as a legitimate counterpart with whom one can jointly advance communication and discovery.

Suggested Citation

  • Takashi Iba, 2026. "Why Is Creative Collaboration With Generative AI Actually Possible? A Theoretical Analysis With Social System Theory and Creative System Theory," Contributions to Economics, in: Francesca Greco & Andrea Fronzetti Colladon & Peter A. Gloor (ed.), Artificial Intelligence and Networks for a Sustainable Future, pages 173-194, Springer.
  • Handle: RePEc:spr:conchp:978-3-032-13458-5_11
    DOI: 10.1007/978-3-032-13458-5_11
    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:conchp:978-3-032-13458-5_11. 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.