doi: 10.18178/JAAI.2024.2.2.173-208
Programming GPT as an Assessment Technology: Identifying the Scientific and Moral Structure of the Unconscious
Albert J. Levis
- Museum of the Creative Process, Manchester, USA
- Manuscript received January 10, 2024
- accepted August 7, 2024
- published August 23, 2024
Abstract
The Formal Theory of Behavior (FT) asserts that emotions are energetic quantities and that the unconscious is an energy and emotional transformation process that is both a scientific and a conflict resolving entity. FT conceptualizes this transformation process as consisting of a syndrome of six emotions. FT identifies four types of conflict resolutions, the relational modalities, as wellness diagnoses. This study uses Large Language Models (LLM) to identify the structure of the unconscious as a syndrome and relational modalities, demonstrating the scientific thesis underlying the unconscious process.<br/>The study trains GPT to recognize FT's distinctions. The trained model is utilized to examine clinical statements, creating stories itself, political speeches, and religious texts. Derived data confirms FT's distinctions, identifying syndromes, relational modalities, and relational pathologies. Implications include improved recognition of unconscious as the atomistic unit of the social sciences and usage of GPT as an assessment technology applied to the analysis of personal samples of creativity.
Keywords
- artificial intelligence
- creative process
- conflict resolution
- wellness diagnoses
- personality assessment
- Formal Theory
How to Cite
Albert J. Levis, "Programming GPT as an Assessment Technology: Identifying the Scientific and Moral Structure of the Unconscious," Journal of Advances in Artificial Intelligence, vol. 2, no. 2, pp. 173-208, 2024. https://doi.org/ 10.18178/JAAI.2024.2.2.173-208
Copyright & License
Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).