Three scenarios of development: a predictive psychobiography of ChatGPT
This study presents a predictive psychobiography of ChatGPT, exploring its developmental trajectory through the lens of psychological theories. Based on Levinson's life structure theory, and using Piaget's stages of cognitive development, Vygotsky's social learning framework, and Erikson's psychosocial stages, the research conceptualizes ChatGPT's evolution from pre-adulthood to a predicted potential middle adulthood, and points out the currently shared life trajectory of AI and humans. The authors examine the coevolutionary relationship between humans and AI, proposing three developmental outcomes: the emergence of Artificial General Intelligence (AGI), a dystopian 'Golem' scenario, or the ethically ambiguous 'Golemagi'. The analysis places AI within the context of the Fourth Industrial Revolution, highlighting cognitive acceleration, the problem of identity formation, and increasing interdependence with humans. It argues that while AI mimics developmental patterns, it lacks intentionality and self-concept, requiring human guardianship to guide its maturation. The study also explores the implications of AI embodiment and regulation, suggesting that ethical guidance and human-centered development are crucial to ensuring beneficial outcomes. This work expands psychobiographical methods to non-human subjects and introduces predictive psychobiography as a reflective framework for anticipating future technological impacts.
Authors
- Virág Rab (ORCID: https://orcid.org/0009-0007-9896-5714)
- Ildikó Jenák
- Ágnes Bálint (ORCID: https://orcid.org/0000-0003-0894-8990)
Institutions
- Institute of Education Sciences (US)
- Institute of Mathematics and Informatics (BG)
- Czech Academy of Sciences, Institute of Mathematics (CZ)
- University of Pecs (HU)
Publication Details
- Journal
- International Review of Psychiatry
- Published
- 2025-07-04
- DOI
- https://doi.org/10.1080/09540261.2025.2529243
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.31
Funders
- Pécsi Tudományegyetem