The Impacts of Medical Artificial Intelligence to Doctor's Professional Autonomy: Challenges and Countermeasures

In the new medical model of "machine-doctor-patient" constructed by the medical artificial intelligence (AI) prediction models, the "independent judgment" and "independent learning" of some doctors will be affected, that is, the authority in medical diagnosis, treatment decision-making, and independent learning will be dissolved, and may even affect the autonomy of patients. This paper proposes three improvement pathways: human-machine cooperation reconstruction, human-machine relationship reconstruction, and embedded shared decision-making in clinical practice. These approaches aim to enhance physicians' professional autonomy and promote a constructive human-AI collaborative relationship. The goal is to both safeguard physicians' professional value and improve the intelligence and humanization of healthcare services, ultimately advancing smart healthcare toward a higher level of collaborative governance.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-05-01
DOI
https://doi.org/10.12014/j.issn.1002-0772.2025.09.04
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

The Impacts of Medical Artificial Intelligence to Doctor's Professional Autonomy: Challenges and Countermeasures

SHILAP Revista de lepidopterología
Artificial Intelligence in Healthcare and Education
article

The Impacts of Medical Artificial Intelligence to Doctor's Professional Autonomy: Challenges and Countermeasures

article en

Abstract

In the new medical model of "machine-doctor-patient" constructed by the medical artificial intelligence (AI) prediction models, the "independent judgment" and "independent learning" of some doctors will be affected, that is, the authority in medical diagnosis, treatment decision-making, and independent learning will be dissolved, and may even affect the autonomy of patients. This paper proposes three improvement pathways: human-machine cooperation reconstruction, human-machine relationship reconstruction, and embedded shared decision-making in clinical practice. These approaches aim to enhance physicians' professional autonomy and promote a constructive human-AI collaborative relationship. The goal is to both safeguard physicians' professional value and improve the intelligence and humanization of healthcare services, ultimately advancing smart healthcare toward a higher level of collaborative governance.

SHILAP Revista de lepidopterología
University of Science and Technology of China (CN)
Openalex Percentile: Top 56%
Artificial Intelligence in Healthcare and Education
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