What are the key challenges of deploying AI models in safety-critical domains such as autonomous vehicles and medical diagnosis?

Deploying AI models in safety-critical domains poses challenges such as ensuring reliability, robustness, and interpretability of the models, addressing ethical and regulatory considerations, and managing risks associated with model failures or uncertainties. Safety-critical applications require rigorous testing, validation, and monitoring to ensure that AI systems operate safely and effectively in real-world scenarios.