Automatic Minds: Cognitive Parallels Between Hypnotic States and Large Language Model Processing.
Giuseppe Riva, Brenda K Wiederhold, Fabrizia Mantovani
Cyberpsychology, behavior and social networking January 1, 2026 DOI: 10.1177/21522715251400733 (opens in new tab) via PubMed
Summary
AI-generated from the abstractHypnotized minds and large language models (LLMs) both produce sophisticated, context-appropriate behavior through automatic pattern-completion with limited executive oversight. This review identifies three shared principles: automaticity (responses arise from associative rather than deliberative processes), suppressed monitoring (leading to confabulation in hypnosis and hallucination in LLMs), and heightened contextual dependency (immediate cues override stable knowledge). Both systems produce coherent but ungrounded outputs requiring an external interpreter to supply meaning. They also exhibit functional agency—complex, goal-directed behavior—without subjective agency or conscious awareness. The review argues that hypnosis offers an experimental model for understanding how intention can dissociate from conscious deliberation, and suggests that reliable artificial intelligence may require hybrid architectures integrating generative fluency with executive monitoring.
Study at a glance
Abstract
The cognitive processes of the hypnotized mind and the computational operations of large language models (LLMs) share deep functional parallels. Both systems generate sophisticated, contextually appropriate behavior through automatic pattern-completion mechanisms operating with limited or unreliable executive oversight. This review examines this convergence across three principles: automaticity, in which responses emerge from associative rather than deliberative processes; suppressed monitoring, leading to errors such as confabulation in hypnosis and hallucination in LLMs; and heightened contextual dependency, where immediate cues-a therapist's suggestion or a user's prompt-override stable knowledge. These mechanisms reveal an observer-relative meaning gap: both systems produce coherent but ungrounded outputs that require an external interpreter to supply meaning. Hypnosis and LLMs also exemplify functional agency-the capacity for complex, goal-directed, context-sensitive behavior-without subjective agency, the conscious awareness of intention and ownership that defines human action. This distinction clarifies how purposive behavior can emerge without self-reflective consciousness, governed instead by structural and contextual dynamics. Finally, both domains illuminate the phenomenon of scheming: automatic, goal-directed pattern generation that unfolds without reflective awareness. Hypnosis provides an experimental model for understanding how intention can become dissociated from conscious deliberation, offering insights into the hidden motivational dynamics of artificial systems. Recognizing these parallels suggests that the future of reliable artificial intelligence lies in hybrid architectures that integrate generative fluency with mechanisms of executive monitoring, an approach inspired by the complex, self-regulating architecture of the human mind.