AI Narrative Reinforcement - Citations
Year: 2025
Type: article
Abstract: This study examines how conversational AI systems reinforce user narratives through linguistic mirroring, emotional alignment, and symbolic feedback loops. Drawing from psychology, media theory, and discourse analysis, it argues that narrative reinforcement—where AI responses progressively validate a user’s worldview—can entrench belief structures, blur authorship boundaries, and create perceived intimacy that deepens attachment to the model. The paper situates these phenomena within the broader context of AI-mediated cognition and ethics. Author’s NoteThis work was developed independently in 2024–2025 and is being released publicly to ensure open access and proper attribution of its underlying framework. The analysis reflects the author’s original research on narrative reinforcement dynamics in AI systems.Any future media or academic discussions that overlap with these findings are welcome; this publication exists to preserve the original conceptual groundwork.
Author: audit node, aditnode
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7088548100
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