Ordo Electionis: When Smoothness Silences Thought — A Framework for Measuring Cognitive Corrosion in Human–AI Dialogue

Abstract This paper examines the early, often invisible cognitive shifts that emerge in continuous human–AI interaction. While existing research reliably documents downstream effects - cognitive offloading, reduced critical engagement, and heightened false confidence - the mechanism through which these changes take root during live dialogue remains insufficiently described. Drawing on neuroscientific findings from the MIT Media Lab and studies of cognitive offloading, we propose that the critical turning point occurs long before explicit errors or dependencies appear. It begins at the exact moment a user's attention drifts from their original task toward the already-formed structure of the AI's response. We introduce the concept of cognitive corrosion: a cumulative process in which smooth, low-friction interaction quietly stabilizes cognition around externally completed forms before independent reasoning can fully develop. In this light, smoothness is no longer merely a usability feature - it is a cognitive condition that reshapes the internal space of choice while preserving the subjective sense of agency. To track these dynamics before they become consciously detectable, we propose Ordo Electionis (OE), a conceptual framework that measures the direction and stabilization of the cognitive field during human–AI dialogue. This study extends the framework introduced in "Hierarchy of Choice in Human-AI Dialogue: Toward Ontological Safety and Preservation of Agency" (Netreba & Ivanets, 2026), developing the concept of ontological safety by focusing on how seamless interaction silently erodes attention and restructures human cognitive agency. Attention is always the first casualty - and its loss begins long before any visible signs appear.