Research Area
Human and Medical Digital Twins
Governed abductive architectures for medical Patient Digital Twins and for human self-modelling, separating surface narrative from mechanism and attractor structure to reduce fluent-but-unsound accounts.
Works in this area (2)
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PreprintConceptual Framework
Human Digital Twins and Self-Knowledge: A Governed Attractor Architecture for Sound Self-Abduction
Large language models embedded in person-modelling systems, and human beings reflecting on themselves, share a structural vulnerability: both can generate fluent, narratively persuasive, yet abductively unsound accounts of a person. Building on a governed abductive architecture developed for…
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PreprintConceptual Framework
From Plausible Narrative to Sound Abduction: A Governed Abductive Architecture for Medical Digital Twins in Multiple Sclerosis Care
Large language models (LLMs) embedded in medical Patient Digital Twins (PDTs) exhibit a systemic vulnerability: they can generate fluent, narratively persuasive, yet abductively unsound clinical explanations. In this context, abductive soundness means that an explanation preserves mechanistic…