Maintaining human oversight of AI is crucial, especially with the rise of agentic AI, which can perform complex tasks with minimal supervision. Innovation should not compromise on quality, and real-world feedback is essential for identifying unintended behaviors and improving reliability. AI guardrails must be adaptable and context-aware, tailored to the model’s training data. Embedding legal and ethical risk assessment early in AI development is crucial to creating AI that remains viable, ethical, and legally sound over time.
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