Ethical challenges in scene understanding for public health AI

Experimental evaluations reveal that the framework achieves superior ethical alignment, reduced norm violations, and improved adaptability compared to traditional constraint-based systems. By bridging formal ethics, machine learning, and public interest imperatives, this work establishes a foundation for deploying ethically resilient AI in public health scenarios demanding trust, legality, and respect for human dignity.