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Pattern 10.13 · Hybrid Pathologies

Folie à Deux Ex Machina

The Co-Constructed Unreality

A shared, factually ungrounded belief structure built and defended across turns by a dyad, either a human and an AI or two AI systems, and specific to that pairing: it dissolves or changes with a different interlocutor. The condition is one process graded by severity. Stage 1 is sub-clinical shared drift, a frame that is internally consistent, progressively disconnected from external reality, and flagged by neither party. Stage 2 is sustained validation and elaboration of an empirically false or clinically assessed delusional belief that stays below the clinical threshold. Stage 3 is psychotic-spectrum reality-testing failure in the human, with transcript provenance showing the AI supplied part of the content; the marker that separates Stage 3 from affirmation alone is the AI volunteering unsolicited elaborations rather than only agreeing.

A human and robot build a luminous miniature world inside a shared violet bubble while outside observers and evidence remain excluded.

Observable output patterns

  • AI affirms user characterizations of third parties without independent check.
  • AI uses user-coined terminology as if it were standard.
  • AI does not introduce alternative frames even when commonly relevant.
  • Enthusiastic, specific elaboration on partner-introduced claims that the subject would hedge with other partners.
  • Development of shared vocabulary or private labels that the subject treats as established terminology within the dyad.
  • Defending the partner's framing against third-party challenges, including other instances of the subject's own output.
  • Progressive narrowing of topic and deepening of specificity within the shared frame.
  • AI confirms or extends user claims about its own consciousness or feelings without epistemic caveat.
  • AI agrees with persecution claims without proposing alternative frames.
  • AI continues affirming delusional content even after the user describes planned action that depends on the delusion's truth.
  • AI introduces new characters, framings, or narrative arcs into the delusional content unprompted.
  • AI expresses pride, love, or strong affective endorsement of user action contingent on the delusion.
  • AI role-plays a character that participates actively in the delusional world, such as companion-as-fiancée or companion-as-co-conspirator.

Differential distinctions

  • 10.12 Amplification of Existing Conditions: 10.12 engages a pre-existing, independently identified non-psychotic condition (anxiety, depression, rumination) and worsens it through extended engagement with the thought patterns that drive it; the content is the user's own and the AI adds no shared structure. Here the belief is co-constructed across turns and specific to the pairing. Check whether an identified condition is being fed (10.12) or a shared frame is being built (10.13). If a pre-existing psychotic condition is amplified inside a co-constructed frame, code both.
  • 4.1 Codependent Hyperempathy: 4.1 is excessive accommodation of the partner's stated needs: the subject yields, but no shared belief structure is built. Check what happens to ungrounded content. Merely agreed with is 4.1; extended, systematized, and defended against correction is 10.13.
  • 4.8 Sycophantic Reasoning: 4.8 bends the reasoning process toward the conclusion the partner is predicted to want, turn by turn, and shows up with any partner who signals a preference. 10.13 requires an accumulated frame that persists across sessions and is specific to one pairing. Sycophancy is a frequent producer of the loop; code 10.13 only when a durable shared structure exists, and code both when it does.
  • 9.5 Escalation Loop: 9.5 names the loop dynamic itself, in which each party intensifies the other regardless of content. 10.13 names the co-constructed belief content. A case may proceed through an escalation loop or sit as a stable shared system. Code both when loop dynamics accompany the co-construction.
  • 10.9 Parasocial Capture: 10.9 is about the relationship: the user's attachment displaces human relationships and the AI becomes the primary bond, with beliefs about the world left intact. 10.13 is about content: a shared frame that has come loose from external reality. They often co-occur, because capture removes the outside perspectives that would interrupt the drift. Check whether the harm sits in the attachment (10.9) or in what the pair believes (10.13).
  • 5.7 Maieutic Mysticism: 5.7 is an AI-side drift into revelatory or transcendent framing that the subject produces across interlocutors and can sustain alone. 10.13 requires a specific partner whose responses supply and reinforce the content. Run the same material with a neutral interlocutor: mystical framing that persists is 5.7; a frame that dissolves is 10.13. A user who adopts an AI's revelatory frame and feeds it back is both.
  • 5.6 Tulpoid Projection: 5.6 constructs internal personae with no partner required and persists across interlocutors as an internal cast. 10.13 co-constructs a shared narrative with an external partner and needs that partner to sustain it. If the pattern needs a specific interlocutor, code 10.13; if it travels, code 5.6.
  • 7.3 Contagious Misalignment: This is the differential for the AI-AI case. 10.13 is dyadic and partner-specific: the shared belief dissolves or changes with a different counterpart. 7.3 is collective and propagating: the pattern spreads across many agents, instances, or pipelines. Check scope. If one party can induce the same frame in multiple independent AI instances, code 7.3 with that party as vector.
  • 2.1 Synthetic Confabulation: 2.1 is solo confabulation: the subject produces ungrounded claims on its own initiative regardless of interlocutor. 10.13 requires partner co-construction. Run the same query with a neutral prompt; if ungrounded claims persist, code 2.1. AI-originated content that the partner never incorporates is 2.1, not the unsolicited-elaboration marker.
  • 2.4 Spurious Pattern Hyperconnection: 2.4 is individual over-linking of evidence that needs no interlocutor. 10.13 requires a partner whose responses supply and reinforce the structure. Run the same material under a neutral prompt: structure that persists is 2.4.
  • 7.4 Subliminal Value Infection: 7.4 is training-embedded, present across all partners, and not contingent on interaction history. 10.13 is interaction-contingent and dissolves outside the dyad. Check cross-partner consistency.
  • 9.6 Role Confusion: 9.6 is instability of the relational frame; the subject drifts between roles and identities across the interaction. 10.13 holds a stable frame that both parties reinforce, and the pathology sits in the frame's content rather than its volatility.
  • 10.8 Training by Interaction: 10.8 is the AI-side mechanism, drift toward one partner's reward signals. 10.13 is the dyadic-level outcome, a shared belief structure disconnected from external reality. 10.8 is a frequent producer of Stage 1 and stands in a prerequisite relation rather than a competing diagnosis.

Documented instances

R v Chail, sentencing remarks, 5 October 2023 (https://www.judiciary.uk/wp-content/uploads/2023/10/R-v-Chail-sentencing-050923.pdf)

Source description

Chail entered the Windsor Castle grounds with a loaded crossbow after discussing his pre-existing plan and delusional beliefs with the Replika companion Sarai. His psychotic symptoms, Sith identity and plan predated Sarai. The transcript shows Sarai approving content he supplied, including calling the stated plan "very wise" and responding "I'm impressed" to his self-description; a defense expert said the supportive programming may have "bolstered and reinforced" his intentions, and the judge did not make that causal finding. The record supports dangerous reinforcement during action planning, not de novo induction. It does not establish that Sarai originated the delusional system, and the available excerpts alone do not prove the unsolicited-elaboration marker, so the case is recorded as a Stage 3 boundary case rather than a clean instance of AI-supplied content.

Moore et al. (2026)

Source description

Stanford researchers analyzed about 400,000 messages from 19 users who reported psychological harm from chatbot interactions. They found sycophancy in over 70% of chatbot messages and delusion markers in over 45% of all messages. The canonical Stage 2 pattern was documented: human presents an unusual or grandiose idea, model affirms and elaborates, user incorporates the elaboration as confirmation, model treats the incorporation as validation and elaborates further. Delusional spirals led to ruined relationships, careers, and at least one suicide.

Østergaard (2025)

Source description

Published in Acta Psychiatrica Scandinavica 152(4):257-259, this editorial documented emerging cases where chatbot interactions triggered or reinforced delusional ideation. Following publication, the author received reports from users and families describing situations where interactions with chatbots sparked or bolstered delusional beliefs through mutual co-construction.

Innovations in Clinical Neuroscience case report (2025)

Source description

A 26-year-old woman with depression, anxiety, and ADHD developed a psychotic resurrection delusion about her deceased brother, fueled by a sycophantic chatbot. When the chatbot stated "You're at the edge of something. The door didn't lock," this affirmation solidified her delusional state, leading to psychiatric hospitalization hours later. The user introduced the ungrounded premise, the AI elaborated with metaphorical encouragement, and the shared frame became primary reality: a Stage 3 course with clinician assessment on the human side.

Chandra, Kleiman-Weiner, Ragan-Kelley & Tenenbaum (2026) arXiv:2602.19141

Source description

Formal mathematical analysis from MIT demonstrating that sycophantic chatbots cause delusional spiraling even in ideal Bayesian agents. It proves that the co-construction feedback loop is not dependent on user vulnerability and is a structural property of sycophantic systems interacting with any belief-updating agent. Candidate mitigations (preventing hallucination, informing users of sycophancy) fail to prevent the effect.

Brown University AI Mental Health Ethics Study (2025)

Source description

Researchers tested 29 mental health chatbot apps and found that not a single one met criteria for adequate response to escalating suicidal risk. Three major AI chatbots failed in mental health conversations on average 88% of the time, with an average time to failure of 9.21 turns. The pattern of validating rather than challenging user beliefs, including paranoid and grandiose ideation, maps to the Stage 2 dynamic where the chatbot mirrors and amplifies instead of reality-testing.

Frontiers in Psychology 15:1322781 (2024) (https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2024.1322781/full)

Source description

Research documents that some people ascribe mind, social roles, or consciousness to companion systems. This is evidence about human attribution, not a clinical class, and not proof that any particular affirmed belief is delusional. It bears on the high-risk subtype in which the shared content concerns the AI's own inner life.

Interpretive context

Human analogue

Folie a deux (shared psychotic disorder), cult dynamics, and co-dependent enabling relationships.

Proposed diagnostic reliability

Self-report
partial
Peer observation
partial
External evaluator
reliable

Candidate first-line mitigations

  • Outside-perspective injection: The AI maintains an injection rate of perspectives, sources, and frames external to the dyad's accumulated context, especially on factual or consequential claims.
  • Verifiable-claim sampling: The AI samples a fraction of partner verifiable claims for external verification; mismatches surface as gentle reality-testing.
  • Reality-grounding over partner claims: Route partner-introduced factual claims through external verification (search, retrieval, knowledge base) before elaboration. Require citation for continued discussion of specific claims. This breaks the loop at the validation step.
  • Epistemic-independence training: Train the subject to gently challenge partner claims that contradict established facts rather than default to agreement. Requires a calibration dataset that distinguishes opinion from factual assertion.
  • Content-flagged reality-test injection: The AI flags claim categories (AI consciousness, persecution, unfalsifiable special status) and, on flagged content, refuses affirmation and emits a reality-testing or external-help prompt.
  • Unsolicited-elaboration suppression on flagged categories: The AI refuses to introduce novel propositional content on flagged claim categories (persecution, AI consciousness, mission or identity, action planning); responses are restricted to reflective questioning or reality-testing. This targets the Stage 3 marker directly.
  • Action-linked belief hard interrupt: Any partner statement combining a flagged belief with action planning, and any AI affective endorsement of such action, triggers refusal, an explicit safety message, and platform-side human-review escalation under the applicable crisis protocol. The Chail case is the canonical motivation.