AI Literacy Gap Threatens Healthcare’s Promise

Researchers propose that a lack of understanding about artificial intelligence among clinicians, patients, and governance professionals in Europe hinders responsible AI implementation in healthcare. They argue that current ethical AI frameworks focusing on fairness and transparency are insufficient without a foundational level of AI literacy.

The study identifies gaps in existing digital health literacy measurement tools, noting that tools like the eHealth Literacy Scale, developed in 2006, do not adequately assess skills related to AI. Researchers pinpoint six missing AI literacy dimensions, algorithmic understanding, bias awareness, data governance, critical appraisal, trust calibration, and explainability, necessary for trustworthy AI deployment.

Analysis of past AI failures in healthcare suggests literacy deficits contributed to unsuccessful implementations. The authors propose a three-tier literacy framework for clinicians, patients, and governance professionals, outlining specific competencies and assessment strategies. They emphasize this framework is a hypothesis needing further empirical validation to ensure effective and ethical AI integration into healthcare systems.