From the Greimasian generative trajectory to generative artificial intelligence: Rethinking the status of the human
By: Marion Colas-Blaise
| ARTICLE INFO: Volume: 11 Issue: 02:Winter 2025 ISSN: 2459-2943 DOI: 10.18680/hss.2025.0022 Pages: 69-96 Lic.: CC BY-NC-ND 4.0 |
KEYWORDS: Generative Trajectory of Meaning Generative Artificial Intelligence Genesis Individuation Mixed enunciative apparatus |
ABSTRACT
This article has as its primary objective to compare generative artificial intelligence (GenAI) with the generative trajectory of meaning developed by A.J. Greimas. We aim to show that, despite similarities, deep learning algorithmic models, which seek to produce verbal and visual texts by involving spaces (latent space, implementation, and visualization spaces), are not generative in the sense understood by semioticians (semiotic square, narrative structures, discoursive structures, actantial conversions, modalizations, aspectualizations…). We will thus ask whether the Greimasian generative trajectory of meaning offers a productive framework for highlighting the specificities of contemporary models of algorithmic processes. Conversely, the study examines whether GenAI can serve as an epistemic lens to gain new insights into the Greimasian generative trajectory. Central to this inquiry are both the becoming of the technical object, its individuation, according to Simondon (genesis of technical objects), and, with regard to the human, a mode of ‘beingwith-it’ in an ‘associated milieu.’ Finally, this question will be reexamined through a mixed, ‘human-machine’ enunciative apparatus. Particular attention will then be paid to the becoming of meaning.
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