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海尔兄弟

A3: The study found that the feedback of the results can improve the accuracy of the user's predictions (reducing the absolute error), thereby improving the performance of working with AI. However, interpretability does not have as much impact on user task performance as it does on trust. This may mean that we should pay more attention to how to effectively use feedback mechanisms to improve the usefulness and effectiveness of AI-assisted decision-making.

被智慧老人制造出来的海尔兄弟，即哥哥琴岛与弟弟海尔，和他们的小伙伴一起旅行冒险。从太平洋跨越到美洲、南极，又从澳洲来到非洲、欧洲，亚洲，最后回到起点。一路上饱览风景名胜的同时，也遇到各种各样的危险，身处不同的险境，在这当中亲身体验自然的神秘与美丽，了解它们背后的故事。可谓融地理、人文、历史等知识于一体。让观者在看的同时，既获得乐趣，又了解到相应的知识，可谓国产科普动画的代表作。　　全长212集的长篇动画《海尔兄弟》由北京红叶电脑动画公司和海尔集团联合投资，形象沿用了海尔集团的标志，并且赋予了新的内涵和故事情节。

海尔兄弟

Q3: How does result feedback and model interpretability affect user task performance?

1995 动画,儿童,冒险更新: 2024-08-03 22:43:23

Q3: How does result feedback and model interpretability affect user task performance?

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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.

The Interpretability of Artificial Intelligence and the Impact of Outcome Feedback on Trust: A Comparative Study

Q3: How does result feedback and model interpretability affect user task performance?

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Xue Zhirong, Designer, Interaction Design, Human-Computer Interaction, Artificial Intelligence, Official Website, Blog, Creator, Author, Engineer, Paper, Product Design, Research, AI, HCI, Design, Learning, Knowledge Base, xuezhirong, UX, Design, Research, AI, HCI, Designer, Engineer, Author, Blog, Papers, Product Design, Study, Learning, User Experience

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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.

The Interpretability of Artificial Intelligence and the Impact of Outcome Feedback on Trust: A Comparative Study | Xue Zhirong's knowledge base

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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.

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

Based on large language model generation, there may be a risk of errors.

A2: Although it is generally believed that the explanatory nature of the model helps to improve user trust, the experimental results show that this enhancement is not significant and not as effective as feedback. In specific cases, such as areas of low expertise, some form of interpretation may result in only a modest increase in appropriate trust.

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Q2: Does explainability necessarily enhance users' trust in AI?

Based on large language model generation, there may be a risk of errors.

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

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To assess trust more accurately, the researchers used behavioral trust (WoA), a measure that takes into account the difference between the user's predictions and the AI's recommendations, and is independent of the model's accuracy. By comparing WoA under different conditions, researchers can analyze the relationship between trust and performance.

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Q2: Does explainability necessarily enhance users' trust in AI?

A3: The study found that the feedback of the results can improve the accuracy of the user's predictions (reducing the absolute error), thereby improving the performance of working with AI. However, interpretability does not have as much impact on user task performance as it does on trust. This may mean that we should pay more attention to how to effectively use feedback mechanisms to improve the usefulness and effectiveness of AI-assisted decision-making.

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海尔兄弟

Q3: How does result feedback and model interpretability affect user task performance?

海尔兄弟动画,儿童,冒险Based on large language model generation, there may be a risk of errors.

Q3: How does result feedback and model interpretability affect user task performance?

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English

Bahasa Indonesia

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海尔兄弟

1995 中国大陆

Based on large language model generation, there may be a risk of errors.

主演: 唐亚男,王江,张美娟,房露,张华,王羊,滕腾,车晓彤,邹赫威,高扬

Q3: How does result feedback and model interpretability affect user task performance?

thesis 1 The researchers found that although it is generally believed that the interpretability of the model can help improve the user's trust in the AI system, in the actual experiment, the global and local interpretability does not lead to a stable and significant trust improvement. Conversely, feedback (i.e., the output of the results) has a more significant effect on increasing user trust in the AI. However, this increased trust does not directly translate into an equivalent improvement in performance. 2 To assess trust more accurately, the researchers used behavioral trust (WoA), a measure that takes into account the difference between the user's predictions and the AI's recommendations, and is independent of the model's accuracy. By comparing WoA under different conditions, researchers can analyze the relationship between trust and performance. 3 User experience 4 Xue Zhirong, Designer, Interaction Design, Human-Computer Interaction, Artificial Intelligence, Official Website, Blog, Creator, Author, Engineer, Paper, Product Design, Research, AI, HCI, Design, Learning, Knowledge Base, xuezhirong, UX, Design, Research, AI, HCI, Designer, Engineer, Author, Blog, Papers, Product Design, Study, Learning, User Experience 5 Interactive 6 Translation 7 Draw inferences 8 The Interpretability of Artificial Intelligence and the Impact of Outcome Feedback on Trust: A Comparative Study 9 The Interpretability of Artificial Intelligence and the Impact of Outcome Feedback on Trust: A Comparative Study | Xue Zhirong's knowledge base