Workshop on Trust and Reliance in AI-Human Teams (TRAIT)-Reference-Cited by-同舟云学术

Workshop on Trust and Reliance in AI-Human Teams (TRAIT)

Published:2023-04-19 Issue: Volume: Page:
ISSN:
Container-title:Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems
language:
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Author:

Bansal Gagan¹^ORCID,Buçinca Zana²^ORCID,Holstein Kenneth³^ORCID,Hullman Jessica⁴^ORCID,Smith-Renner Alison Marie⁵^ORCID,Stumpf Simone⁶^ORCID,Wu Sherry³^ORCID

Affiliation:

1. Microsoft Research, United States

2. School of Engineering and Applied Sciences, Harvard University, United States

3. Human-Computer Interaction Institute, Carnegie Mellon University, United States

4. Computer Science, Northwestern University, United States

5. AI Organization, Dataminr, United States

6. School of Computing Science, University of Glasgow, United Kingdom

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3544549.3573831

Reference26 articles.

1. Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance

2. The Role of Explanations on Trust and Reliance in Clinical Decision Support Systems

3. Erin K Chiou and John D Lee . 2021 . Trusting Automation: Designing for Responsivity and Resilience. Human Factors (2021), 00187208211009995. Erin K Chiou and John D Lee. 2021. Trusting Automation: Designing for Responsivity and Resilience. Human Factors (2021), 00187208211009995.

4. Henriette Cramer , Vanessa Evers , Satyan Ramlal , Maarten Van Someren , Lloyd Rutledge , Natalia Stash , Lora Aroyo , and Bob Wielinga . 2008. The effects of transparency on trust in and acceptance of a content-based art recommender. User Modeling and User-adapted interaction 18, 5 ( 2008 ), 455. Henriette Cramer, Vanessa Evers, Satyan Ramlal, Maarten Van Someren, Lloyd Rutledge, Natalia Stash, Lora Aroyo, and Bob Wielinga. 2008. The effects of transparency on trust in and acceptance of a content-based art recommender. User Modeling and User-adapted interaction 18, 5 (2008), 455.

5. A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores