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<p>AI systems are rapidly approaching expert-level diagnostic reasoning; however, management reasoning —the art of translating diagnoses into personalized care—remains distinctly human. While both are forms of clinical judgment, they emphasize different skills: diagnosis is a categorization task that answers “what’s wrong?”; management is a prioritization task that answers “what should we do?” Medicine has long privileged diagnostic virtuosity. We drill differential diagnosis in morning report but rarely teach with equal rigor how to navigate real-world trade-offs for patients who value independence over longevity. This imbalance leaves us vulnerable as AI masters pattern recognition. Management reasoning requires what AI cannot currently replicate: integrating human values, navigating system constraints, and building therapeutic relationships. These fundamentally human skills—not diagnostic prowess—should anchor our professional identity. To secure medicine’s future, we argue for a deliberate reorientation of medical education and clinical culture. Making space to teach and showcase management reasoning is not just an educational priority; it is essential for defending clinician judgment, relational care, and public trust as AI reshapes medicine’s social contract. The goal is not merely finding the “right” answer but preparing clinicians to find the best answer for each unique patient. This is how human care remains truly human.</p>

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Elevating Management Reasoning to Preserve Professional Identity in the AI Era

  • 期刊论文

  • 发表日期：

    2026年1月20日

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  • R. Logan Jones,
  • Adam Rodman,
  • Andrew S. Parsons

摘要

AI systems are rapidly approaching expert-level diagnostic reasoning; however, management reasoning —the art of translating diagnoses into personalized care—remains distinctly human. While both are forms of clinical judgment, they emphasize different skills: diagnosis is a categorization task that answers “what’s wrong?”; management is a prioritization task that answers “what should we do?” Medicine has long privileged diagnostic virtuosity. We drill differential diagnosis in morning report but rarely teach with equal rigor how to navigate real-world trade-offs for patients who value independence over longevity. This imbalance leaves us vulnerable as AI masters pattern recognition. Management reasoning requires what AI cannot currently replicate: integrating human values, navigating system constraints, and building therapeutic relationships. These fundamentally human skills—not diagnostic prowess—should anchor our professional identity. To secure medicine’s future, we argue for a deliberate reorientation of medical education and clinical culture. Making space to teach and showcase management reasoning is not just an educational priority; it is essential for defending clinician judgment, relational care, and public trust as AI reshapes medicine’s social contract. The goal is not merely finding the “right” answer but preparing clinicians to find the best answer for each unique patient. This is how human care remains truly human.