The subpersonal cognitive level (Andler, 2023)—conceived in terms of connectionist and computational models within the brain—lies primarily in the domain of scientific inquiry, particularly disciplines that can rigorously investigate non-symbolic, mechanistic processes. This level, which we might term “subcognitive” or “proto-cognitive,” requires an approach grounded in the physical and computational sciences, as it involves a type of processing that operates without the symbolic meaning structures addressed by psychoanalysis and psychology. Sciences like computational neuroscience, neurovision, systems neuroscience, and related fields are uniquely positioned to elucidate this subpersonal level due to their ability to model, measure, and test neural dynamics in ways that reveal fundamental, non-conscious mechanisms.
While psychoanalysis and psychology excel in elucidating symbolic, emotional, and functional layers of the psyche, they are inherently limited when it comes to explaining the subpersonal level. These fields focus on subjective experience, interpretation, and meaning, areas that necessitate a symbolic framework and an interpretative lens.
However, the subpersonal level does not operate within a symbolic order or a language of desire, repression, or consciousness. It is fundamentally about mechanical, pre-interpretative processing. Understanding these basic processes requires a scientific approach that can directly measure neural patterns, sensory integration, and computational outputs. Psychoanalysis, although invaluable for exploring depth psychology, cannot penetrate the non-symbolic, algorithmic nature of subpersonal processes. Similarly, psychology, which relies on observable behavior and cognitive function, cannot adequately address the granular, mechanistic operations happening beyond the level of conscious awareness or symbolic meaning.
Cybercapitalism, particularly in its current digital form, exploits both the subpersonal and symbolic levels of human cognition to unprecedented extents, leveraging technology and data science to access, manipulate, and even automate responses within these domains. The combination of granular data on individual digital activity and insights from psychological sciences enables corporations to influence and predict consumer behavior with astonishing precision.
Andler, D. (2023). Intelligence artificielle, intelligence humaine : la double énigme. Paris : Gallimard.
L. Poenaru
Oct. 30, 2024
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