Human Reliance on Machine Learning Models When Performance Feedback is Limited: Heuristics and Risks-Reference-Cited by-同舟云学术

Human Reliance on Machine Learning Models When Performance Feedback is Limited: Heuristics and Risks

Published:2021-05-06 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
language:
Short-container-title:

Author:

Lu Zhuoran¹,Yin Ming¹

Affiliation:

1. Purdue University, United States

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3411764.3445562

Reference66 articles.

1. Guidelines for Human-AI Interaction

2. Bias on the web

3. Updates in Human-AI Teams: Understanding and Addressing the Performance/Compatibility Tradeoff

4. Gagan Bansal Tongshuang Wu Joyce Zhu Raymond Fok Besmira Nushi Ece Kamar Marco Tulio Ribeiro and Daniel S Weld. 2020. Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance. (2020). arxiv:2006.14779 Gagan Bansal Tongshuang Wu Joyce Zhu Raymond Fok Besmira Nushi Ece Kamar Marco Tulio Ribeiro and Daniel S Weld. 2020. Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance. (2020). arxiv:2006.14779

Cited by 61 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A closer look at how experience, task domain, and self-confidence influence reliance towards algorithms;Applied Ergonomics;2024-11

2. To Err Is AI! Debugging as an Intervention to Facilitate Appropriate Reliance on AI Systems;Proceedings of the 35th ACM Conference on Hypertext and Social Media;2024-09-10

3. You Can Only Verify When You Know the Answer: Feature-Based Explanations Reduce Overreliance on AI for Easy Decisions, but Not for Hard Ones;Proceedings of Mensch und Computer 2024;2024-09

4. Explainability for Transparent Conversational Information-Seeking;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

5. "I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust;The 2024 ACM Conference on Fairness, Accountability, and Transparency;2024-06-03