A hospital's AI system must give personalized treatment suggestions and explain the reasoning in a way that clinicians and patients can understand. Which human-centered design principle does this reflect?

Explainability is the correct answer because it directly addresses the need for the AI system to provide understandable reasoning for its suggestions. In a clinical setting, both clinicians and patients need to comprehend how a treatment suggestion was derived to build trust and facilitate informed decision-making. Privacy and security are crucial for protecting patient data but don't directly relate to the interpretability of the AI's output. Fairness ensures the AI treats all individuals equitably, preventing bias, but doesn't explain the reasoning behind specific recommendations. Data governance refers to the overall management of data, including its quality and usage, which is foundational but not the principle focused on making AI decisions transparent.