#trust-calibration News & Analysis

3 articles tagged with #trust-calibration. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AIBearisharXiv – CS AI · Jun 237/10

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Trust in Generative AI for Health Information Consumption and the Effect of Learned Dependency: An Experimental Study

A randomized experimental study of 338 participants reveals that users who develop learned dependency on generative AI for health information exhibit weaker trust calibration and increased susceptibility to incorrect outputs. While information accuracy generally increases trust in AI-generated health content, highly dependent users show diminished ability to discern accuracy, and visual attention cues failed to mitigate this overtrust vulnerability.

AINeutralarXiv – CS AI · May 286/10

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AI, Take the Wheel: What Drives Delegation and Trust in Human-Computer Cooperative Question Answering?

A research study examines how humans decide to trust and rely on AI systems in collaborative question-answering tasks, identifying two distinct reliance patterns: delegation (autonomous AI action) and adoption (evaluating AI suggestions). The findings reveal humans make suboptimal trust decisions, both under-utilizing correct AI suggestions and over-relying on misleading AI outputs, with confirmation bias playing a significant role in trust calibration failures.

AINeutralarXiv – CS AI · May 286/10

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The Decision to Verify: How Warmth and User Characteristics Shape Reliance on Conversational Agents for Information Search

A research study examines how users interact with conversational AI systems when fact-checking is accessible through hybrid search interfaces. The findings reveal that users continue to over-rely on AI answers despite having web search available, with verification behavior driven primarily by user characteristics like prior trust rather than answer quality, while conversational warmth indirectly increases reliance by boosting agreement with incorrect responses.