← All publications
Cogn. Tech. WorkJournal Article2024
Understanding the Influence of AI Autonomy on AI Explainability in Human-AI Teams Using a Mixed Methods Approach
Allyson I. Hauptman, Beau G. Schelble, Christopher Flathmann, Wen Duan, Nathan J. McNeese
Cognition, Technology and Work, 26, 435-455 (2024)
PDF coming soon
The free author-version PDF for this paper hasn't been uploaded yet. In the meantime, use the publisher link above, or email me and I'll send you a copy directly. Research should be accessible to everyone.
BibTeX
@article{hauptman2024understanding,
title = {Understanding the Influence of AI Autonomy on AI Explainability in Human-AI Teams Using a Mixed Methods Approach},
author = {Hauptman, Allyson I. and Schelble, Beau G. and Flathmann, Christopher and Duan, Wen and McNeese, Nathan J.},
year = {2024},
journal = {Cognition, Technology and Work},
note = {26, 435-455},
doi = {10.1007/s10111-024-00765-7}
}Topics
explainabilityadaptive autonomymethods
Related Work
PACM HCI·2026
A Mixed Methods Approach to Analyzing the Role of AI Teammates in Transition Phases
Proceedings of the ACM on Human-Computer Interaction
Springer·2026
Modeling Human Behavior in Cybersecurity: Leveraging Structural Equation Modeling to Address Cognitive Biases and Enhance Defense Strategies
Foundations of Cyber Deception, Springer Nature
AI & Ethics·2025
Ethical Adaptation: Exploring the Use of Adaptive Autonomy in the Design of Ethical AI Teammates in Healthcare
AI and Ethics
HFES·2025
Leveraging Generative AI to Create Lightweight Simulations for Far-Future Autonomous Teammates
Proceedings of the Human Factors and Ergonomics Society Annual Meeting