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A Trust Model for Human-Machine Interaction in Virtual Reality.

Lida Ghaemi Dizaji, Nusrat Z Zenia, Yaoping Hu

    IEEE Transactions on Visualization and Computer Graphics
    |April 1, 2026
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new model to measure real-time human trust in machines within virtual reality (VR), incorporating human and machine reliability for better human-machine interaction. Objective data proved more effective than subjective data in tracking trust dynamics.

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    Area of Science:

    • Human-computer interaction
    • Virtual Reality (VR)
    • Trust in artificial intelligence

    Background:

    • Effective human-machine interaction in virtual reality (VR) hinges on human trust in machines.
    • Existing trust frameworks lack real-time metrics and adequate consideration of human/machine reliability.

    Purpose of the Study:

    • To propose and evaluate a novel trust model with metrics for all layers of trust dynamics.
    • To incorporate human and machine reliability into the trust model for VR applications.

    Main Methods:

    • Developed a trust model with metrics to capture trust dynamics across all layers.
    • Evaluated the model using objective and subjective data from two VR use-cases.
    • Assessed the impact of human and machine reliability on trust dynamics.

    Main Results:

    • The proposed model effectively captures trust dynamics, considering both human and machine reliability.
    • Objective data demonstrated higher sensitivity in tracking trust dynamics compared to subjective data.
    • The model's pertinence was confirmed through evaluation in VR use-cases.

    Conclusions:

    • The developed trust model is suitable for real-time measurement of trust dynamics in VR.
    • The model's integration of reliability factors enhances its applicability.
    • Findings suggest the model can facilitate the design of trustworthy and adaptive VR systems.