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AI and System Evolution in CPD: Integrating CHAT with a Unified Theory of Emergent System Evolution
Summary
Artificial intelligence (AI) is reshaping healthcare learning systems. This study offers a framework to understand AI's impact on professional development, promoting adaptive and resilient learning ecosystems.
Area of Science:
- Healthcare education
- Sociotechnical systems
- Artificial intelligence applications
Background:
- Artificial intelligence (AI) is transforming clinical decision-making and team collaboration.
- Existing continuing professional development (CPD) research often overlooks the broader sociotechnical implications of AI in healthcare.
- A comprehensive framework is needed to understand AI-driven changes in healthcare learning environments.
Purpose of the Study:
- To examine how AI induces contradictions within and between activity systems in healthcare.
- To explain how these contradictions accelerate structural changes in learning, collaboration, identity, and governance.
- To provide a framework for designing adaptive, ethical, and resilient AI-enhanced learning ecosystems.
Main Methods:
- Integration of Cultural-Historical Activity Theory (CHAT) and a Unified Theory of Emergent System Evolution.
- Analysis of AI's influence on tools, rules, roles, and community structures within activity systems.
- Application of a four-phase evolutionary model (egocentric, technocentric, ecocentric, holocentric) to learning system development.
Main Results:
- AI amplifies tensions and creates new forms of distributed cognition across multiple levels (individual to societal).
- Contradictions induced by AI accelerate structural changes in healthcare learning and professional development.
- The integrated framework facilitates understanding of AI's transformative effects on healthcare activity systems.
Conclusions:
- The proposed framework aids in designing AI-enhanced learning ecosystems that are adaptive, relational, ethical, and resilient.
- Understanding AI-induced contradictions is crucial for navigating changes in clinical practice and CPD.
- This research offers a conceptual toolset for fostering expansive learning in AI-transformed healthcare.
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