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AI Explainability, Trust, and Calibration / Explanation Form Design and Comprehension Effects

Users struggle to build long-term trust when facing erroneous AI recommendations.

lightbulbPractical problemExplanation Form Design and Comprehension Effects

Users struggle to build long-term trust when facing erroneous AI recommendations.

IUI '23It Seems Smart, but It Acts Stupid: Development of Trust in AI Advice in a Repeated Legal Decision-Making Task

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Noise or privacy protection weakens emotion recognition accuracy and explanation reliability.

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Users misjudge symptoms due to health information on social media, leading to incorrect self-diagnosis.

CHI '25Mining Evidence about Your Symptoms: Mitigating Availability Bias in Online Self-Diagnosis

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Users distrust or misunderstand explanations of autonomous driving system behavior.

CHI '25People Attribute Purpose to Autonomous Vehicles When Explaining Their Behavior: Insights from Cognitive Science for Explainable AI

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Users feel anxious about health information from search engines, especially when misinformation triggers panic.

CHI '25How the Algorithmic Transparency of Search Engines Influences Health Anxiety: The Mediating Effects of Trust in Online Health Information Search

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Users struggle to obtain context-relevant, personalized stress management advice.

CHI '25CounterStress: Enhancing Stress Coping Planning through Counterfactual Explanations in Personal Informatics

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Data annotation is time-consuming, and existing tools struggle to align with users' cognitive approaches and annotation intent.

UIST '24MOCHA: Model Optimization through Collaborative Human-AI Alignment

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