Tainan University of Technology

Bounding Repetition in Clinical AI Safety Arguments from Fail-Operational to Dynamic Trajectory Governance

Safety arguments for clinical artificial intelligence are stated per encounter: a proposal is admitted or refused against the patient's state at one moment. We show that such a formalism cannot express repetition. In a released deterministic kernel the treatment history is retain...

Bounding Inaction in Clinical AI Safety Arguments from Fail-Safe to Fail-Operational

Safety arguments for clinical artificial intelligence are stated in one direction: the system must not do what it should not do. Other fields have recognised the complement - automotive functional safety requires fail-operational rather than merely fail-safe behaviour, and the sa...

A Human-Centric Deterministic-Kernel Probabilistic-Shell Architecture with Invariants that Confine Clinical AI Decision Authority

Medical artificial intelligence faces a structural tension: capability arises from probabilistic models, whereas safety requires guarantees those models cannot give. We implement and verify an architecture in which the probabilistic component holds no execution authority. A deter...

A Human-Centric Deterministic-Kernel Probabilistic-Shell Architecture with Invariants that Confine Clinical AI Decision Authority

Medical artificial intelligence faces a structural tension: capability arises from probabilistic models, whereas safety requires guarantees those models cannot give. We implement and verify an architecture in which the probabilistic component holds no execution authority. A deter...