Non-EKU Spark Talk: Beyond the Algorithm: Building Trustworthy, Fair, and Useful AI in Health and Higher Education

Presenter: Dr. Samuel Kakraba

Artificial intelligence is increasingly shaping decisions in healthcare, public health, research, and education. But strong technical performance alone does not guarantee that an AI system is trustworthy, fair, understandable, or useful in the settings where people rely on it. 

This Spark Talk explores three practical questions: How do we know an AI model is trustworthy? How do we know it is fair? And what can higher education learn from the ways AI is being developed and used in healthcare? Through accessible examples from public-health surveillance, drug discovery, cancer-risk assessment, and mental-health prediction, participants will examine how researchers test AI systems, identify potential biases, explain how predictions are made, and consider whether a model works equitably across different communities. 

The session will connect these real-world health applications to broader questions facing colleges and universities. Participants will consider how AI literacy can help students and faculty ask better questions, evaluate AI-generated information responsibly, collaborate across disciplines, and use emerging tools as supports for learning rather than as opaque authorities. No technical background is required; the discussion will emphasize practical concepts, examples, and questions that participants can apply in their own disciplines and institutional settings.