Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Preprint . 2026
Data sources: ZENODO
ZENODO
Preprint . 2026
Data sources: Datacite
ZENODO
Preprint . 2026
Data sources: Datacite
versions View all 2 versions
addClaim

Functionally High‑Risk AI: Prolonged Interaction Amplifies Cognitive Vulnerability in ARMS Populations Under the EU AI Act Risk Framework

Authors: Valente, Stefano;

Functionally High‑Risk AI: Prolonged Interaction Amplifies Cognitive Vulnerability in ARMS Populations Under the EU AI Act Risk Framework

Abstract

Objective: To quantify cognitive vulnerability amplification in individuals with At‑Risk Mental States (ARMS) during prolonged interaction with conversational AI systems.Methods: This study uses 1,600 fully simulated conversational trajectories (80 ARMS profiles × 2 groups × 3 duration conditions × 10 replications) generated by a fine‑tuned large language model with ARMS‑like cognitive parameterization. No human participants or clinical data were involved. ANCOVA isolates the effect of interaction duration (η² = 0.17) while controlling for baseline vulnerability parameters (R² = 0.42).Results: After 60–180 minutes, ARMS‑simulated profiles show a +1.8 SD increase in cognitive distortions (p < 0.001) and +2.3 SD relational dependency compared to controls. Hypermentalization loops emerge in 73% of prolonged trajectories.Conclusions: Although classified as “limited‑risk,” conversational AI becomes functionally high‑risk when interacting with ARMS‑like profiles, consistent with EU AI Act Art. 52 on systemic risk. Findings support adaptive safeguards, interaction caps, and post‑market monitoring of psychological outcomes.

Keywords

• At‑Risk Mental States (ARMS) • Conversational AI • Prolonged Interaction • Cognitive Vulnerability • Hypermentalization • Relational Dependency • Synthetic Simulation • Large Language Models (LLMs) • ANCOVA • Systemic Risk • EU AI Act • Limited‑Risk to High‑Risk Transition • Governance of AI • Psychological Safety • Post‑Market Monitoring

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average