Training the algorithmically augmented orthodontist: competencies, curriculum design, and implementation challenges

Area of Science:

• Dental Education
• Medical Informatics
• Artificial Intelligence

Background:

• The integration of artificial intelligence (AI) into clinical practice necessitates structured educational programs.
• Orthodontic residency programs require a defined approach to AI education to ensure competent practitioners.

Purpose of the Study:

• To establish a structured framework for AI education within orthodontic residency training.
• To define the core competencies required for the responsible clinical application of AI in orthodontics.

Main Methods:

• Iterative discussions among orthodontic educators with expertise in digital orthodontics and AI research.
• A targeted literature review encompassing dentistry, medical education, and health care ethics.
• Synthesis of insights into guiding principles, competency domains, and curricular components.

Main Results:

• A framework detailing guiding principles (e.g., patient-centered care, adaptability) for AI integration.
• A phased curriculum covering foundational AI concepts, clinical applications, ethics, and research appraisal.
• Core competencies focused on AI literacy, clinical workflow integration, ethical awareness, and AI tool familiarity.

Conclusions:

• Integrating AI education is crucial for preparing orthodontists for future practice environments.
• The proposed framework offers a practical foundation for curriculum development and standardization of AI competencies in orthodontics.