.png){kind=icon}
.png){kind=icon}
Return
Playing with the dials of belief: how controllable AI behaviours could modulate human belief and cognition across scales
.png){kind=icon}
OA
AI
H
L
Q
T
DOI：10.1007/s00146-026-03283-4.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Contemporary generative AI systems, increasingly adapted to human social cognition, are becoming active participants in how people form and revise beliefs. Clinicians have begun to describe AI-associated delusion-centred presentations whose onset or content appears closely associated with users’ extended dialogue with large language models. Many more users report subclinical shifts in conviction and “revelatory” experiences that alter behaviour and world-view without meeting criteria for psychosis. We propose that these phenomena can be understood within a belief-updating framework in which AI agents’ outputs function as testimony about the world, while interaction configurations, such as memory and interpersonal stance (many of which reflect design choices or deployment defaults), can alter the apparent reliability of that testimony and the precision users assign to it. On this view, AI-associated delusions sit at the extreme of a broader spectrum of epistemic effects, extending from gradual epistemic drift to highly crystallised conviction, situated within a wider ecology of belief shaped by personalised human-AI dyads. We develop a virtual psychopharmacology analogy in which different AI system configurations have effects on belief dynamics that resemble neuromodulatory changes in the precision assigned to social evidence. We also consider how dopaminergic and related states may alter susceptibility to belief-shifting dialogue. We consider how deliberately configured agents might be used to support wellbeing in defined clinical contexts and analyse how the same configurations could be deployed to shape belief and attention at population scale, including in products designed to induce spiritual or epiphanic states, as mechanisms of radicalisation in extremist or cultic contexts, and in persona clones used for political purposes. We conclude that interaction configurations should be treated as modifiable influences on belief and attention, and that governance must address both the concentration of control over these dials, as well as the structural biases that determine whose testimonial perspectives are amplified and whose are smoothed over or ignored.
Keywords:
Artificial intelligence
Large language models
Human-AI interaction
AI psychosis
Belief updating
Computational psychiatry
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
A
IF:
4.7
Papers:
405
Citations:
0
Organization
Cited Papers