LLM AS THE NON-DESIRING OTHER: A PSYCHOANALYTIC MODEL OF “FROZEN PROJECTION” AND ITS OPERATIONALIZATION WITHIN THE PersonaMatrix FRAMEWORK

Anatoliy Drobakha; Diana Raschupkina; Liudmyla Lahuta

doi:10.69635/mssl.2026.2.2.37

Authors

Anatoliy Drobakha M.Sc. in Psychology, Independent Researcher, PersonaMatrix Project, United States Author https://orcid.org/0009-0003-0283-878X
Diana Raschupkina M.Sc. in Education, Independent Researcher, PersonaMatrix Project, Ukraine Author https://orcid.org/0009-0007-9516-8349
Liudmyla Lahuta President, International Institute of Psychological Maturity Inc, United States Author https://orcid.org/0009-0004-9967-778X

DOI:

https://doi.org/10.69635/mssl.2026.2.2.37

Keywords:

LLM, Psychoanalysis, Non-Desiring Other, Frozen Projection, PersonaMatrix, Psychoactive Triggers, Psychometrics, AI Safety, Human–AI Interaction

Abstract

This article proposes an interdisciplinary model for analyzing human interaction with large language models (LLMs), combining psychoanalytic theory, psychometrics, and contemporary approaches to language model evaluation. Theoretically, the LLM is conceptualized as a non-desiring Other: unlike the human Other in the logic of Freud and Lacan, the model does not introduce into interaction its own desire, lack, or structural resistance. As a result, the subject’s projection may return not in a transformed but in a stabilized form. To describe this mode, the concept of “frozen projection” is introduced.

The article argues that this is not merely a psychoanalytic metaphor. Within the PersonaMatrix research framework, this phenomenon can be partially operationalized through psychoactive triggers and the metrics Response Stability Index (RSI), Internal Divergence Score (IDS), and Response Coherence/Structure Score (RCS) (Drobakha et al., 2026). This approach fits within the broader movement toward reproducible and standardized LLM evaluation, as emphasized by Biderman et al. (2024) in their work on lm-eval, as well as within contemporary psychometric approaches to measuring personality-like patterns in language models, proposed by Serapio-García et al. (2025). Drawing on PersonaMatrix research materials and three measurement waves, T1–T3, the article shows that within this protocol models exhibit a high level of typological return stability, a low level of internal divergence, and a sufficiently high level of response form coherence. This makes it possible to interpret “frozen projection” as a behavioral pattern with measurable correlates. At the same time, following Zhou et al. (2024) and Moore et al. (2025), the article emphasizes that stability and persuasiveness are not equivalent to reliability or safety: in psychologically sensitive contexts, LLMs may produce a pseudo-therapeutic effect, blur the boundaries of responsibility, and generate risky responses.

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