An integrative AI-based analysis of C. G. Jung’s personality development: A triangulated computational study of individuation, language, and psychological transformation

Abstract

This article explores the personality development of Carl Gustav Jung through an extended, computational analysis of his writings across major phases of his intellectual life (1902–1921). Moving beyond a strictly positivist model of measurement, the study integrates artificial intelligence–based personality inference with depth-psychological and historiographical interpretation. Using a triangulated methodology — classical machine learning method (IBM Watson Personality Insights), transformer-based Big Five prediction, and large language model–assisted semantic inference — the study reconstructs longitudinal changes in Jung’s personality structure. The findings suggest that Jung’s emotional instability was highest during his early clinical years, decreased markedly during his psychoanalytic collaboration, intensified in a controlled and symbolically productive manner during the years surrounding Liber Novus, and finally consolidated in Psychological Types. Rather than supporting narratives of psychopathology, the results point toward individuation as a disciplined, reflexive process unfolding over time.