An AI governance committee is evaluating whether to permit the use of synthetic training data generated by a generative AI model to supplement scarce real training data for a medical diagnosis AI. Which risk should receive the HIGHEST priority in this evaluation?

B is correct because in medical AI, the most dangerous failure modes are often rare clinical presentations (uncommon but life-threatening conditions). Synthetic data generated by a model that learned from the same scarce real data may not represent these rare but critical cases, and may actually amplify the scarcity problem by generating only typical cases. A model trained on such synthetic data may underperform exactly when accuracy matters most. Computational cost (A), IP status (C), and environmental impact (D) are legitimate concerns but are secondary to the patient safety risk of inadequate coverage of rare but critical presentations.