Answer: Explainability

The scenario describes an AI system that must provide the rationale behind its recommendations and make those insights accessible to both doctors and patients. This directly aligns with the human-centered design principle of **Explainability**. **Why Explainability is the correct answer:** 1. **Transparency in Decision-Making**: The requirement to provide the rationale behind recommendations ensures that the AI's decision-making process is transparent, allowing users to understand how and why specific treatment suggestions are generated. 2. **Accessibility of Insights**: Making insights accessible to both medical professionals and patients emphasizes the need for clear, interpretable outputs that different stakeholders can comprehend, which is a core aspect of explainable AI. 3. **Trust and Informed Decision-Making**: In healthcare contexts, explainability builds trust by enabling doctors to validate recommendations and patients to participate meaningfully in their care decisions. 4. **Alignment with AWS AI Principles**: AWS emphasizes explainability as a key responsible AI principle, particularly for high-stakes applications like healthcare where understanding AI outputs is critical for safety and efficacy. **Why other options are less suitable:** - **B: Privacy and Security**: While important in healthcare, this principle focuses on protecting sensitive data rather than explaining AI decisions. - **C: Fairness**: This addresses bias mitigation and equitable treatment, not the transparency of decision rationale. - **D: Data Governance**: This involves managing data quality, lineage, and compliance, not specifically about making AI insights understandable to end-users. The scenario's emphasis on rationale and accessibility makes Explainability the most appropriate human-centered design principle.

Author: LeetQuiz Editorial Team