A sociological reading of human-robot trust concludes that robots are relied on rather than trusted, and outlines a research agenda treating trust as practical engagement.
Mapping User Trust in Vision Language Models: Research Landscape, Challenges, and Prospects
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abstract
The rapid adoption of Vision Language Models (VLMs), pre-trained on large image-text and video-text datasets, calls for protecting and informing users about when to trust these systems. This survey reviews studies on trust dynamics in user-VLM interactions, through a multi-disciplinary taxonomy encompassing different cognitive science capabilities, collaboration modes, and agent behaviours. Literature insights and findings from a workshop with prospective VLM users inform preliminary requirements for future VLM trust studies.
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What Can Robots Teach Us About Trust and Reliance? An interdisciplinary dialogue between Social Sciences and Social Robotics
A sociological reading of human-robot trust concludes that robots are relied on rather than trusted, and outlines a research agenda treating trust as practical engagement.