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From doing to being: Generative AI, workplace affordances, and professional identity
1Department of Medical Education, The University of Melbourne, Melbourne, Australia.
Medical Teacher
|July 28, 2026
Summary
Generative artificial intelligence (AI) impacts medical education by altering workplace learning environments. This shift may affect how clinicians develop professionally, necessitating a focus beyond technical tool use.
Area of Science:
- Medical Education
- Artificial Intelligence
- Clinical Learning Environments
Background:
- Generative artificial intelligence (AI) is significantly influencing medical education.
- Current discourse primarily focuses on AI tool use, faculty training, and learning risks.
- Learner socialization, role modeling, and professional identity formation are crucial in clinical settings.
Purpose of the Study:
- To examine the impact of AI on the conditions necessary for clinician development.
- To shift the discourse on AI in medical education towards its effects on workplace learning and professional identity.
- To explore how AI-driven changes in uncertainty affect clinical learning environments.
Main Methods:
- Qualitative analysis of discourse on AI in medical education.
- Conceptual framework integrating social learning theories and workplace communities of practice.
- Exploration of the role of uncertainty in clinical learning and professional development.
Main Results:
- AI may relocate uncertainty, a key driver of workplace learning.
- This relocation can alter the affordances of clinical learning environments.
- Potential impact on learner socialization, role modeling, and professional identity formation.
Conclusions:
- The integration of AI in medical education requires a broader perspective beyond technical aspects.
- Understanding AI's effect on workplace learning dynamics is crucial for effective clinician development.
- Further research is needed to explore strategies for supporting professional identity formation in AI-influenced clinical environments.
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