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Peer-reviewedCC BYWorld Journal of Otorhinolaryngology-Head and Neck Surgery

Understanding and Mitigating Bias From Artificial Intelligence in Otolaryngology: A State‐of‐the‐Art Review

  • Matthew T. Ryan1
  • David A. Gudis1
  1. 1Department of Otolaryngology–Head & Neck Surgery Columbia University Irving Medical Center New York New York USA
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Abstract

Objective To provide an overview of potential biases resulting from the utilization of artificial intelligence (AI) in otolaryngology and techniques to mitigate them. Data Sources Literature review and expert opinion. Conclusions AI promises to fundamentally transform medicine. This review highlights how biases can be introduced inadvertently at every level of AI application and development and how those biases risk undermining the intent and beneficence of these tools. A number of techniques which can be used to mitigate these biases are discussed. Ultimately, understanding the limitations and appropriate applications of this technology is critical to ensuring it is utilized equitably and efficaciously.

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Cite

BibTeXRIS
BibTeX
@article{ryan2026understanding,
  title = {{Understanding and Mitigating Bias From Artificial Intelligence in Otolaryngology: A State‐of‐the‐Art Review}},
  author = {Matthew T. Ryan and David A. Gudis},
  journal = {World Journal of Otorhinolaryngology-Head and Neck Surgery},
  year = {2026},
  month = oct,
  doi = {10.1002/wjo2.70093},
  url = {https://doi.org/10.1002/wjo2.70093},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Understanding and Mitigating Bias From Artificial Intelligence in Otolaryngology: A State‐of‐the‐Art Review
AU  - Matthew T. Ryan
AU  - David A. Gudis
PY  - 2026
DA  - 2026/10/23
JO  - World Journal of Otorhinolaryngology-Head and Neck Surgery
DO  - 10.1002/wjo2.70093
UR  - https://doi.org/10.1002/wjo2.70093
AB  - Objective To provide an overview of potential biases resulting from the utilization of artificial intelligence (AI) in otolaryngology and techniques to mitigate them. Data Sources Literature review and expert opinion. Conclusions AI promises to fundamentally transform medicine. This review highlights how biases can be introduced inadvertently at every level of AI application and development and how those biases risk undermining the intent and beneficence of these tools. A number of techniques which can be used to mitigate these biases are discussed. Ultimately, understanding the limitations and appropriate applications of this technology is critical to ensuring it is utilized equitably and efficaciously.
SN  - 2589-1081
SN  - 2095-8811
ER  -