October 1, 2025Open Access

A closer look at how large language models trust humans: patterns and biases

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LLM trust development mirrors human trust in many contexts, suggesting shared dynamics in trust formation.
Across 43,200 simulations, trustworthiness dimensions were significant predictors of LLM trust, often influenced by demographics.
The approach utilized established behavioral theories to analyze how AI agents estimate trust based on human characteristics.
Findings indicate a need for monitoring biases in AI interaction to prevent harmful outcomes in trust-dependent applications.

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Study examines trust based on competence, benevolence, and integrity in AI interactions, suggesting biases exist.

Lerman et al. (2025) studied this question.

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