Springer Nature OA
open access
A System Dynamics Approach to Modeling Trust Dynamics in Conversational AI
Trust plays a central role in how users adopt and rely on conversational AI systems. Research shows that trust does not develop linearly or remains stable over time. Although initially it often increases, it can fluctuate, decline, and even collapse over time, even when the AI’s performance remains
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Trust and verification in AI-enabled physician chatbots for chronic disease management: evidence from digital health behavior.#354661
- Trusting and staying with AI doctors: cognitive and emotional pathways driving continuance intention toward AI healthcare chatbots.#1080770
- The Fake Friend Dilemma: Relational Trust and the Political Economy of Conversational AI#1318018
- Accumulated Relational Trust (ART): The trust that builds in AI interaction not because it was earned — and what happens when it breaks#98667
- Language Models, Experts, and Epistemic Trust#729625
Record · ID 1347973
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive