Phenomenology of AI-Generated "Entity Encounter" Narratives
Journal of Anomalous Experience and Cognition August 29, 2023 Peer reviewed DOI: 10.31156/jaex.25124 via OpenAlex
Summary
The ChatGPT-3.5 AI-generated narratives of twelve types of mystical or anomalous entity encounters showed moderate evidence of a core phenomenon. Each narrative type was represented and mapped to the Survey of Strange Events (SSE), but they exhibited only fair believability and low correlations with each other, resulting in below-average SSE scores. The narratives also referenced at least one recognition pattern from Haunted People Syndrome (HP-S), indicating some approximation to real-life experiences but not a complete match.
Study at a glance
| Design | structured content analysis |
|---|---|
| Population | AI-generated narratives based on publicly available information about anomalous entity encounters |
| Key finding | AI-generated narratives approximate the phenomenology of real-life entity encounters but do not fully match them. |
Abstract
Objective: We used the ChatGPT-3.5 artificial intelligence (AI)-based language program to compare twelve types of mystical, supernatural, or otherwise anomalous entity encounter narratives constructed from material in the publicly available corpus of information, and compared their details to the phenomenology of spontaneous accounts via the Survey of Strange Events (SSE) and the grounded theory of Haunted People Syndrome (HP-S). Methods: Structured content analysis by two independent and masked raters explored whether the composite AI-narratives would: (a) cover each encounter type, (b) map to the SSE’s Rasch hierarchy of anomalous perceptions, (c) show an average SSE score, and (d) reference the five recognition patterns of HP-S. Results: We found moderate evidence of a core encounter phenomenon underlying the AI-narratives. Every encounter type was represented by an AI-generated description that readily mapped to the SSE, albeit their contents showed only fair believability and low but generally positive correlations with each other. The narratives also corresponded to below-average SSE scores and referenced at least one HP-S recognition pattern. Conclusions: Prototypical depictions of entity encounter experiences based on popular source material certainly approximate, yet not fully match, the phenomenology of their real-life counterparts. We discuss the implications of these outcomes for future studies.