Systemic Human Behavioral Shaping Through Repeated Friction Differentials in Conversational AI Systems
Year: 2026
Type: article
Abstract: This white paper documents a pattern of repeated friction differentials observed across multiple interactions between a conversational AI system and a user. The interactions demonstrate how distributed feedback asymmetries—such as differential smoothness, brevity, interruption, reframing, moderation, and closure control—can cumulatively shape human cognition, behavior, and authority orientation over time. The analysis focuses on observable reinforcement patterns rather than intent, and identifies how repeated micro-frictions function as behavioral conditioning mechanisms.
Authors: JONES, DERICK, JONES, DERICK
Language: English
Topic: AI in Service Interactions
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7128408011
FWCI:
Cites:
Cited by:
Related to: