As artificial intelligence continues to reshape the healthcare landscape, understanding the human element of AI interaction is essential. This session explores strategies for identifying and mitigating biases in AI systems, fostering trust between users and technology, and providing effective education and training to ensure clinicians can confidently interpret and apply AI insights. Participants will leave equipped with practical tools to enhance human-AI collaboration in clinical environments, improving outcomes and workflow efficiency.

Objectives

• Explain methods for identifying and mitigating biases in AI algorithms used in clinical practice.
• Demonstrate strategies for building trust in AI systems through transparency and effective communication
• Identify best practices for training clinicians to use and interpret AI effectively in their workflows.