A mechanistic model of trust based on neural information processing

Scott E. Allen, Ren\'e F. Kizilcec and A. David Redish

Papers from arXiv.org

Abstract: Trust is central to human social interactions, manifesting in actions that make one vulnerable to another. We argue that trust will thus depend on the decision-making processes that arise in neural systems. Building on advances in the cognitive neuroscience of decision making, we propose a mechanistic model of trust arising from multiple parallel systems that perform distinct, complementary information processing. Because each system learns via different mechanisms, trust can be created (or destroyed) in multiple ways. This systems-level taxonomy of information representations provides a principled basis for differentiating forms of trust, linking them to specific learning processes, and generating testable predictions about their expression in behavior. By situating trust within a broader theory of neural decision systems, our account unifies diverse findings across psychology, neuroscience, and the social sciences, and offers a foundation for explaining how humans develop, maintain, and repair trust in a complex social world.

Date: 2024-01, Revised 2025-09
New Economics Papers: this item is included in nep-cbe and nep-evo
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2401.08064 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2401.08064

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().