lightbulbPractical problemExplanation, Control, and Trust in Recommendation Systems
Non-expert users struggle to judge whether algorithm-recommended visualizations are reliable.AI Explainability, Trust, and Calibration / Explanation, Control, and Trust in Recommendation Systems
Non-expert users struggle to judge whether algorithm-recommended visualizations are reliable.
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lightbulbPractical problemExplanation, Control, and Trust in Recommendation Systems
Users lack trust in recommendation system content and do not understand recommendation rationales.lightbulbPractical problemExplanation, Control, and Trust in Recommendation Systems
Adolescents struggle to understand and trust algorithmically recommended learning content.IUI '23Steering Recommendations and Visualising Its Impact: Effects on Adolescents’ Trust in E-Learning Platforms
lightbulbPractical problemExplanation, Control, and Trust in Recommendation Systems
Users have a trust crisis toward health recommendation systems based on social media data.lightbulbPractical problemExplanation, Control, and Trust in Recommendation Systems
Users do not trust recommendation results because the embedding models used by recommender systems are too difficult to explain.lightbulbPractical problemExplanation, Control, and Trust in Recommendation Systems
Users face heavy burden managing recommended file operations one by one in cloud storage.lightbulbPractical problemExplanation, Control, and Trust in Recommendation Systems
Users have insufficient trust in recommendation systems, especially during cold-start phases.Related papers
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