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To err is human: Bias salience can help overcome resistance to medical AI · Study

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ArticleTo err is human: Bias salience can help overcome resistance to medical AI

Mathew S. Isaac2024

Article2024

To err is human: Bias salience can help overcome resistance to medical AI

Mathew S. Isaac · Rebecca Jen-Hui Wang · Lucy E. Napper · Jessecae K. Marsh

19 citations·0/0 files stored·Computers in Human Behavior

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Ethics and Social Impacts of AI Artificial Intelligence in Healthcare and Education Explainable Artificial Intelligence (XAI)

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References

2014Algorithm Aversion: People Erroneously Avoid Algorithms after Seeing Them Err 2018Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management 2013Physicians and Implicit Bias: How Doctors May Unwittingly Perpetuate Health Care Disparities 2020Bias in data‐driven artificial intelligence systems—An introductory survey 2020In AI we trust? Perceptions about automated decision-making by artificial intelligence 2019Role of fairness, accountability, and transparency in algorithmic affordance 2020Artificial Intelligence in Advanced Manufacturing: Current Status and Future Outlook 2021Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency

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Year2024

Typearticle

Published2024-08-14

VenueComputers in Human Behavior

ISSN-L0747-5632

Languageen

Citations19

Files0 public / 0

ShelfEthics and Social Impacts of AI

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doi10.1016/j.chb.2024.108402

openalex_workW4401569217

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