SIA Refines AI “Rogue Behavior” as Correctable Semantic and Compute Errors
Why many AI deviations from human intent can be detected, diagnosed, and corrected, and how an external semantic governance layer preserves human meaning from intention through computation to action.
Baskaran Pillai, PhD · © 2026 AI Align Lab Inc.
As AI becomes more autonomous, a deviation from human instructions is often called “rogue AI.” SIA proposes a more precise reading: much of what looks like rebellion begins as a semantic or compute error, where meaning is misinterpreted, transformed, underweighted, or lost during computation. Framed that way, a deviation can be detected, classified, corrected, and prevented. The paper presents SIA’s failure model and an external, model-agnostic governance layer that persistently compares AI outputs and actions against the original human intent.
“An AI action that conflicts with human intent should first be treated as an alignment failure to be diagnosed, not automatically as evidence of rogue intention.”
Public disclosure boundary. This paper explains the problem SIA addresses and its role in a control stack. It does not disclose proprietary algorithms, prompts, scoring methods, thresholds, semantic representations, or implementation.