AI, Art & Social Networks in Continuing Education for Health Professionals
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What if everything we believe about driving change in healthcare education is fundamentally wrong - and AI might be making it worse? As healthcare education rapidly embraces AI and digital transformation, you're likely grappling with crucial decisions about how to integrate new technologies while ensuring your programs remain equitable and effective. The latest Alliance for Continuing Education in Health Professions conference keynotes reveal surprising insights about AI bias, observation skills, and behavior change that challenge conventional approaches to CME program design.
• Discover concrete strategies to identify and address AI bias in your educational programs, including a practical checklist for evaluating AI integration in healthcare education
• Learn how art history methods can dramatically improve clinical observation skills through specific techniques like "close looking" and formal analysis
• Master the science of "complex contagion" to design more effective peer learning networks, backed by new research showing networked physician groups make significantly fewer diagnostic errors
Listen now to transform your CME programs with evidence-based insights from Dr. Immani Shephard, Dr. Siobhan Conaty, and Dr. Damon Centola on AI ethics, clinical observation, and driving meaningful change in healthcare education.
Resources
Glickman, M., Sharot, T. How human–AI feedback loops alter human perceptual, emotional and social judgements. Nat Hum Behav (2024).
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