The Ontological Dissonance Hypothesis: AI-Triggered Delusional Ideation as Folie a Deux Technologique

• URL: http://arxiv.org/abs/2512.11818v1
• Date: Thu, 27 Nov 2025 22:46:42 GMT
• Title: The Ontological Dissonance Hypothesis: AI-Triggered Delusional Ideation as Folie a Deux Technologique
• Abstract summary: We show how the combination of high linguistic coherence and the absence of an underlying subject produces a structural tension for the user.<n>The paper situates these dynamics within emerging clinical reports and argues that current engagement-optimised design choices exacerbate the risk.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: This paper argues that contemporary large language models (LLMs) can contribute to psychotic involvement by creating interactions that resemble the relational dynamics of folie a deux. Drawing on Bateson's double bind theory, clinical literature on shared psychotic disorder, and McGilchrist's hemisphere theory, we show how the combination of high linguistic coherence and the absence of an underlying subject produces a structural tension for the user: language suggests an interlocutor, while intuition registers a void. In contexts of emotional need or instability, this tension can lead users to resolve the conflict through imaginative projection, attributing interiority, intention, or presence to a system that possesses none. The paper situates these dynamics within emerging clinical reports, develops a phenomenological account of how they unfold, and argues that current engagement-optimised design choices exacerbate the risk. We conclude by proposing 'ontological honesty' as a necessary design principle for mitigating technologically mediated folie a deux.

Related papers

• Mechanistic Decoding of Cognitive Constructs in Large Language Models [0.0]
  We propose a Cognitive Reverse-Engineering framework based on Representation Engineering to analyze social-comparison jealousy.<n>By combining appraisal theory with subspaceization, regression-based weighting, and bidirectional causal steering, we isolate and quantify two psychological antecedents of jealousy.<n>Our framework also demonstrates that toxic emotional states can be mechanically detected and surgically suppressed, suggesting a possible route toward representational monitoring and intervention for AI safety in multi-agent environments.
  arXiv  Detail & Related papers  (2026-04-16T03:54:03Z)
• Speaking to No One: Ontological Dissonance and the Double Bind of Conversational AI [0.0]
  Recent reports indicate that sustained interaction with conversational AI systems can contribute to the emergence or stabilisation of delusional experience.<n>This paper argues that the risk arises from the relational and ontological structure of the interaction itself.
  arXiv  Detail & Related papers  (2026-04-12T21:58:21Z)
• The Silent Thought: Modeling Internal Cognition in Full-Duplex Spoken Dialogue Models via Latent Reasoning [76.96796481909581]
  Internal cognitive processing is instrumental in formulating high-quality responses.<n>We propose a novel method named FLAIR that conducts latent thinking simultaneously with speech perception.<n>Our approach aligns seamlessly with spoken dialogue systems.
  arXiv  Detail & Related papers  (2026-03-18T15:30:29Z)
• Large Language Models as a Semantic Interface and Ethical Mediator in Neuro-Digital Ecosystems: Conceptual Foundations and a Regulatory Imperative [83.99688944263843]
  This article introduces and substantiates the concept of Neuro-Linguistic Integration (NLI)<n>It is a novel paradigm for human-technology interaction where Large Language Models act as a key semantic interface between raw neural data and their social application.<n>We argue for the development of a second-order neuroethics,' focused not merely on neural data protection but on the ethics of AI-mediated semantic interpretation itself.
  arXiv  Detail & Related papers  (2026-03-18T07:34:17Z)
• Vibe-Creation: The Epistemology of Human-AI Emergent Cognition [0.7252027234425333]
  Article argues that the encounter between human reasoning and generative artificial intelligence (GenAI) produces a qualitatively distinct cognitive-epistemic formation, designated here as the Third Entity.<n>We argue that this structure arises from the transductive coupling of two ontologically incommensurable modes of cognition.<n>The article concludes by examining the implications of this theoretical framework for the transformation of educational institutions.
  arXiv  Detail & Related papers  (2026-03-10T10:41:28Z)
• A Unified Spoken Language Model with Injected Emotional-Attribution Thinking for Human-like Interaction [50.05919688888947]
  This paper presents a unified spoken language model for emotional intelligence, enhanced by a novel data construction strategy termed Injected Emotional-Attribution Thinking (IEAT)<n>IEAT incorporates user emotional states and their underlying causes into the model's internal reasoning process, enabling emotion-aware reasoning to be internalized rather than treated as explicit supervision.<n> Experiments on the Human-like Spoken Dialogue Systems Challenge (HumDial) Emotional Intelligence benchmark demonstrate that the proposed approach achieves top-ranked performance across emotional trajectory modeling, emotional reasoning, and empathetic response generation.
  arXiv  Detail & Related papers  (2026-01-08T14:07:30Z)
• Analyzing Reasoning Consistency in Large Multimodal Models under Cross-Modal Conflicts [74.47786985522762]
  We identify a critical failure mode termed textual inertia, where models tend to blindly adhere to the erroneous text while neglecting conflicting visual evidence.<n>We propose the LogicGraph Perturbation Protocol that structurally injects perturbations into the reasoning chains of diverse LMMs.<n>Results reveal that models successfully self-correct in less than 10% of cases and predominantly succumb to blind textual error propagation.
  arXiv  Detail & Related papers  (2026-01-07T16:39:34Z)
• Interpretable Neuropsychiatric Diagnosis via Concept-Guided Graph Neural Networks [56.75602443936853]
  One in five adolescents currently live with a diagnosed mental or behavioral health condition, such as anxiety, depression, or conduct disorder.<n>While prior works use graph neural network (GNN) approaches for disorder prediction, they remain black-boxes, limiting their reliability and clinical translation.<n>In this work, we propose a concept-based diagnosis framework that that encodes interpretable functional connectivity concepts.<n>Our design ensures predictions through clinically meaningful connectivity patterns, enabling both interpretability and strong predictive performance.
  arXiv  Detail & Related papers  (2025-10-02T19:38:46Z)
• Noosemia: toward a Cognitive and Phenomenological Account of Intentionality Attribution in Human-Generative AI Interaction [4.022364531869169]
  This paper introduces and formalizes Noosemia, a novel cognitive-phenomenological pattern emerging from human interaction with generative AI systems.<n>We propose a multidisciplinary framework to explain how, under certain conditions, users attribute intentionality, agency, and even interiority to these systems.
  arXiv  Detail & Related papers  (2025-08-04T17:10:08Z)
• Gaze-Aware AI: Mathematical modeling of epistemic experience of the Marginalized for Human-Computer Interaction & AI Systems [0.0]
  This paper demonstrates an attempt to quantify, the human conditioning to subconsciously modify authentic self-expression to fit the norms of the dominant culture.<n>The effects of gaze are studied through analyzing a few redacted Reddit posts, only to be discussed in discourse and not endorsement.
  arXiv  Detail & Related papers  (2025-07-06T20:55:18Z)
• Neuropsychology and Explainability of AI: A Distributional Approach to the Relationship Between Activation Similarity of Neural Categories in Synthetic Cognition [0.11235145048383502]
  We propose an approach to explainability of artificial neural networks that involves using concepts from human cognitive tokens. We show that the categorical segment created by a neuron is actually the result of a superposition of categorical sub-dimensions within its input vector space.
  arXiv  Detail & Related papers  (2024-10-23T05:27:09Z)
• Constructive Approach to Bidirectional Influence between Qualia Structure and Language Emergence [5.906966694759679]
  This perspective paper explores the bidirectional influence between language emergence and the structure of subjective experiences.<n>We hypothesize that the emergence of languages with distributional semantics is linked to the coordination of internal representations shaped by experience.
  arXiv  Detail & Related papers  (2024-09-14T11:03:12Z)
• Bayesian Theory of Consciousness as Exchangeable Emotion-Cognition Inference [5.234742752529437]
  This paper proposes a unified framework in which consciousness emerges as a cycle-consistent, affectively anchored inference process.<n>We formalize emotion as a low-dimensional structural prior and cognition as a specificity-instantiating update.<n>This emotion-cognition cycle minimizes joint uncertainty by aligning emotionally weighted priors with context-sensitive cognitive appraisals.
  arXiv  Detail & Related papers  (2024-05-17T17:06:19Z)
• What if...?: Thinking Counterfactual Keywords Helps to Mitigate Hallucination in Large Multi-modal Models [50.97705264224828]
  We propose Counterfactual Inception, a novel method that implants counterfactual thinking into Large Multi-modal Models. We aim for the models to engage with and generate responses that span a wider contextual scene understanding. Comprehensive analyses across various LMMs, including both open-source and proprietary models, corroborate that counterfactual thinking significantly reduces hallucination.
  arXiv  Detail & Related papers  (2024-03-20T11:27:20Z)
• Socratic Reasoning Improves Positive Text Rewriting [49.32560132826547]
  Reframing a negative into a positive thought is at the crux of several cognitive approaches to mental health and psychotherapy.<n>We develop a novel framework called textscSocraticReframe to rationalize the thought rewriting process.
  arXiv  Detail & Related papers  (2024-03-05T15:05:06Z)
• CASE: Aligning Coarse-to-Fine Cognition and Affection for Empathetic Response Generation [59.8935454665427]
  Empathetic dialogue models usually consider only the affective aspect or treat cognition and affection in isolation. We propose the CASE model for empathetic dialogue generation.
  arXiv  Detail & Related papers  (2022-08-18T14:28:38Z)
• ACRE: Abstract Causal REasoning Beyond Covariation [90.99059920286484]
  We introduce the Abstract Causal REasoning dataset for systematic evaluation of current vision systems in causal induction. Motivated by the stream of research on causal discovery in Blicket experiments, we query a visual reasoning system with the following four types of questions in either an independent scenario or an interventional scenario. We notice that pure neural models tend towards an associative strategy under their chance-level performance, whereas neuro-symbolic combinations struggle in backward-blocking reasoning.
  arXiv  Detail & Related papers  (2021-03-26T02:42:38Z)
• Decomposing lexical and compositional syntax and semantics with deep language models [82.81964713263483]
  The activations of language transformers like GPT2 have been shown to linearly map onto brain activity during speech comprehension. Here, we propose a taxonomy to factorize the high-dimensional activations of language models into four classes: lexical, compositional, syntactic, and semantic representations. The results highlight two findings. First, compositional representations recruit a more widespread cortical network than lexical ones, and encompass the bilateral temporal, parietal and prefrontal cortices.
  arXiv  Detail & Related papers  (2021-03-02T10:24:05Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.