Explainable Artificial Intelligence: Evaluating the Objective and Subjective Impacts of xAI on Human-Agent Interaction
Author:
Affiliation:
1. College of Computing, Georgia Institute of Technology, Atlanta, GA, USA
Funder
MIT
NASA
the National Science Foundation
Publisher
Informa UK Limited
Subject
Computer Science Applications,Human-Computer Interaction,Human Factors and Ergonomics
Link
https://www.tandfonline.com/doi/pdf/10.1080/10447318.2022.2101698
Reference80 articles.
1. Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2. Interpretable Machine Learning Tools: A Survey
3. Barnett, A. J., Schwartz, F. R., Tao, C., Chen, C., Ren, Y., Lo, J. Y., et al. (2021). Iaia-bl: A case-based interpretable deep learning model for classification of mass lesions in digital mammography. arXiv preprint arXiv:2103.12308.
4. Measurement Instruments for the Anthropomorphism, Animacy, Likeability, Perceived Intelligence, and Perceived Safety of Robots
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