lightbulb现实痛点XAI 解释与适当依赖校准用户对机器学习模型的信任因指标冲突而降低,影响模型采用率。CHI '22When Confidence Meets Accuracy: Exploring the Effects of Multiple Performance Indicators on Trust in Machine Learning Models
lightbulb现实痛点XAI 解释与适当依赖校准用户在使用AI系统时难以理解其建议,可能导致过度信任或拒绝其推荐。IUI '25Is Conversational XAI All You Need? Human-AI Decision Making With a Conversational XAI Assistant
lightbulb现实痛点XAI 解释与适当依赖校准用户难以在与AI的持续交互中建立长期学习能力。IUI '25Benefits of Machine Learning Explanations: Improved Learning in an AI-assisted Sequence Prediction Task
lightbulb现实痛点XAI 解释与适当依赖校准用户不理解AI建议且决策中过度依赖AI,导致错误风险增加。IUI '25The Influence of Curiosity Traits and On-Demand Explanations in AI-Assisted Decision-Making
lightbulb现实痛点XAI 解释与适当依赖校准用户无法从AI解释中有效学习,导致过度依赖AI和技能退化。CHI '25Contrastive Explanations That Anticipate Human Misconceptions Can Improve Human Decision-Making Skills
lightbulb现实痛点XAI 解释与适当依赖校准用户因AI解释不清或误解而难以信任智能系统甚至做出错误决策。CHI '25(Mis)Communicating with our AI Systems
lightbulb现实痛点XAI 解释与适当依赖校准用户很难理解无处不在计算和可穿戴技术中AI的决策过程。UbiComp '24XAI for U: Explainable AI for Ubiquitous, Pervasive and Wearable Computing