At the end of this session, the participant will be able to:

• Demonstrate an understanding of the advantages of virtual, augmented, and mixed reality over traditional simulation.
• Recognize the limitations of immersive technologies when used to deliver medical simulation.
• Identify the physiological and emotional effects on participants during immersive and traditional simulation.

At the end of this session, the participant will be able to:

• Evaluate the benefits of integrating playful interaction methods into healthcare education for improving learner engagement.
• Analyze differences among concepts of reality, virtual reality, simulation, and serious gaming in healthcare education.
• Demonstrate an understanding of the key principles of gamification and nudging, and their value in healthcare.

Discuss and summarize key learning points. 

At the end of this session, the participant will be able to:

• Evaluate the transformative potential and critical risks of AI in medicine, including breakthrough applications (AlphaFold, multiagent public health systems) alongside challenges of algorithmic hallucinations and data privacy vulnerabilities.
• Analyze insights from patient diagnosis narratives (autism, end-of-life care) to understand emotional care journeys and identify how AI tools can enhance rather than compromise the human elements of medical encounters while maintaining patient trust and safety.
• Develop evidence-based strategies for implementing AI in clinical practice that leverage empathy research and mental health collaboration insights to strengthen patient-provider relationships while establishing appropriate safeguards against AI-related risks.

At the end of this session, the participant will be able to:

• Summarize the historical developments of the scientific understanding of human attention.
• Identify the role of laboratory-based experimental psychology in codifying conceptions of human attentional behavior.
• Express the importance of alternative conceptions of attention, particularly in relation to intersubjective encounters.

Discuss and summarize key learning points. 

Outline of key learning points from Day 1.

At the end of this session, the participant will be able to:

• Explain the concept and need for a "human in the loop."
• Describe the impact of AI on foundational competencies in medical education.
• Identify strategies for integrating AI education to balance technology and humanism.

At the end of this session, the participant will be able to:

• Employ a narrative approach to reflecting on the opportunities and challenges of AI-assisted medical education research.
• Develop a personal philosophy for whether and how to use AI in medical education research.

At the end of this session, the participant will be able to:

• Demonstrate an understanding of how patient expectations provide an ethical guardrail to using AI in care.
• Identify how to learn from computers that outperform humans and the implied messages we send patients by using them.

Discuss and summarize key learning points.

At the end of this session, the participant will be able to:

• Analyze case examples of algorithmic bias in radiology to identify cultural and ethical implications.

At the end of this session, the participant will be able to:

• Assess the effectiveness of implementing VR-based training in a lower-middle-income hospital setting.

At the end of this session, the participant will be able to:

• Evaluate the effectiveness of combining AI and AR with traditional simulation in overcoming ethical and cultural barriers in obstetrics training.

At the end of this session, the participant will be able to:

• Demonstrate an understanding of the history of the concept of empathy as it relates to the emotional experiences of medical students. 
• Demonstrate an understanding of the relationship between the psychoanalytic concept of countertransference and the current views of empathic communication.
• Recognize how AI-generated patients and supervisors can improve empathy training, as well as the potential risks to be mitigated.

At the end of this session, the participant will be able to:

• Develop familiarity with using mixed reality for medical simulation.
• Demonstrate an understanding of how to acquire low-cost mixed reality simulation software.
• Practice leading a mixed reality medical simulator.

At the end of this session, the participant will be able to:

• Apply design thinking methods to analyze and creatively solve challenges in healthcare using emerging technologies such as AR, VR, and AI.
• Evaluate inclusive design principles for creating accessible, human-centered, virtual healthcare environments.
• Practice collaborative ideation and rapid prototyping techniques to address real-world challenges in patient engagement, behavioral health, and workforce development. 

At the end of this session, the participant will be able to:

• Describe the phenomenology of durational attention.
• Test the use of “protocols” of sensory awareness.
• Reflect on the use of “open attention” in diagnostic settings.

At the end of this session, the participant will be able to:

• Describe at least three governance practices that support the ethical use of AI in their professional life. 
• Analyze at least two case examples of AI applications and distinguish between effective and ineffective uses.
• Develop a framework for integrating AI-human collaboration into service delivery, team dynamics, and operational workflows.
• Select and justify the most appropriate AI models or applications for at least three distinct use cases in their professional context, articulating key trade-offs.

Summarize the key learning points.