The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
“Who goes first? Influences of human-AI workflow on decision making in clinical imaging,”
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From Human-AI collaboration is not very collaborative yet: a taxonomy of interaction patterns in AI-assisted decision making from a systematic review (2025) · cites this paper as Fogliato et al., 2022
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Mitigating bias in algorithmic hiring: evaluating claims and practices
Raghavan, M., Barocas, S., Kleinberg, J., & Levy, K. (2020) · Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency · doi:10.1145/3351095.3372828 · Cited by 845
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance
Bansal, G., Wu, T., Zhou, J., Fok, R., Nushi, B., Kamar, E., Ribeiro, M. T., & Weld, D. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445717 · Cited by 757 · cited 4×
“The adoption of these tools has fostered a scholarly effort on designing human-AI collaborations for optimal team decision making [4, 41, 59, 89].”
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“…we begin our project with an open-ended semi-structured interview [50] with six domain experts as a formative study to gather information on 1) the clinicians’ daily practice of sepsis decision making, and 2) the user experience and user needs of AI-based sepsis decision support systems.”
BackgroundThe Typing Cure: Experiences with Large Language Model Chatbots for Mental Health Support
Song, I., Pendse, S. R., Kumar, N., & De Choudhury, M. (2024) · arXiv · doi:10.48550/arxiv.2401.14362 · Cited by 64
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“For example, in high-stake scenarios such as in the medical [39, 61, 67, 97], legal [6, 81, 86, 131], and financial [27, 36, 43, 45, 46] domains, individuals tend to exhibit a preference for human decision-makers over AI systems.”
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Metadata
- Authors
- Fogliato, R., Chappidi, S., Lungren, M., Fisher, P., Wilson, D., Fitzke, M., Parkinson, M., Horvitz, E., Inkpen, K., & Nushi, B.
- Affiliations
- Carnegie Mellon University, USA
- University of Virginia, USA
- Stanford, USA
- Antech Imaging Services, USA
- Mars Digital Technologies, Germany
- Mars Digital Technologies, USA
- Microsoft Research, USA
- Venue
- 2022 ACM Conference on Fairness Accountability and Transparency
- Publisher
- ACM
- Published
- 2022-06-20
- Pages
- 1362-1374
- Cited by
- 103
- References
- 31
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