Semantic Drift and the Stability of Operator Control in Reasoning-Class Decision Support Systems
The article investigates the fundamental problem of ensuring the stability of operator control and preserving goal-targeting in hybrid human-machine decision support systems (DSS) of a new generation. Based on a two-month continuous longitudinal experiment on the joint design of a monograph-format textual array, the latent phenomenon of semantic context drift in large language models of deep logical reasoning (Reasoning LLMs) is verified and described. A mathematical model of interaction in the human-machine interface is proposed, and an original metric is introduced - the operator control stability coefficient, which takes into account the non-linear contextual pressure of hidden reasoni...
| Authors | M. L. Kaluzhsky, V. A. Efirov |
|---|---|
| Primary category | cs.AI |
| Published | 8 July 2026 |
| Last updated at source | 8 July 2026 |
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