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Q1: How does feedback affect users' trust in AI?

outcome

The results show that feedback has a more significant impact on improving users' trust in AI than explainability, but this enhanced trust does not lead to a corresponding performance improvement. Further exploration suggests that feedback induces users to over-trust (i.e., accept the AI's suggestions when it is wrong) or distrust (ignore the AI's suggestions when it is correct), which may negate the benefits of increased trust, leading to a "trust-performance paradox". The researchers call for future research to focus on how to design strategies to ensure that explanations foster appropriate trust to improve the efficiency of human-robot collaboration.

Personal insights

Draw inferences

A1: According to research, feedback (e.g. result output) is a key factor influencing user trust. It is the most significant and reliable way to increase user trust in AI behavior.

thesis 综合

[原创]RVC微调底模-悦 f048K

会员专属使用帮助宝藏模型 Xue Zhirong is a designer, engineer, and author of several books; Founder of the Design Open Source Community, Co-founder of MiX Copilot; Committed to making the world a better place with design and technology. This knowledge base will update AI, HCI and other content, including news, papers, presentations, sharing, etc.G Problem finding

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RVC模型女生

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女生模型模型工坊精品模型宝藏模型 Xue Zhirong is a designer, engineer, and author of several books; Founder of the Design Open Source Community, Co-founder of MiX Copilot; Committed to making the world a better place with design and technology. This knowledge base will update AI, HCI and other content, including news, papers, presentations, sharing, etc.G E

The researchers conducted two sets of experiments ("Predict the speed-dating outcomes and get up to $6 (takes less than 20 min)" and a similar Prolific experiment) in which participants interacted with the AI system in a task of predicting the outcome of a dating to explore the impact of model explainability and feedback on user trust in AI and prediction accuracy. The results show that although explainability (e.g., global and local interpretation) does not significantly improve trust, feedback can most consistently and significantly improve behavioral trust. However, increased trust does not necessarily lead to the same level of performance gains, i.e., there is a "trust-performance paradox". Exploratory analysis reveals the mechanisms behind this phenomenon.

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thesis 综合