The Who in XAI: How AI Background Shapes Perceptions of AI Explanations-Reference-Cited by-同舟云学术

The Who in XAI: How AI Background Shapes Perceptions of AI Explanations

Published:2024-05-11 Issue: Volume:104 Page:1-32
ISSN:
Container-title:Proceedings of the CHI Conference on Human Factors in Computing Systems
language:
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Author:

Ehsan Upol¹^ORCID,Passi Samir²^ORCID,Liao Q. Vera³^ORCID,Chan Larry⁴^ORCID,Lee I-Hsiang⁵^ORCID,Muller Michael⁶^ORCID,Riedl Mark O⁷^ORCID

Affiliation:

1. Interactive Computing, Georgia Institute of Technology, United States

2. Microsoft, United States

3. Microsoft Research, Canada

4. Illumio, United States

5. School of Industrial & Systems Engineering, Georgia Institute of Technology, United States

6. Human AI Collaboration, IBM Research, United States

7. Georgia Institute of Technology, United States

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3613904.3642474

Reference168 articles.

1. COGAM: Measuring and Moderating Cognitive Load in Machine Learning Model Explanations

2. Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)

3. P Agre. 1997. Toward a critical technical practice: Lessons learned in trying to reform AI in Bowker. G., Star, S., Turner, W., and Gasser, L., eds, Social Science, Technical Systems and Cooperative Work: Beyond the Great Divide, Erlbaum (1997).

4. Philip Agre and Philip E Agre. 1997. Computation and human experience. Cambridge University Press.

5. Alan Agresti. 2003. Categorical data analysis. Vol. 482. John Wiley & Sons.

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