Model safety encompasses the practices and protocols designed to ensure AI systems operate reliably, ethically, and without unintended harm. It involves rigorous testing, bias mitigation, and alignment with human values. Developers benefit from reduced liability, users gain trustworthy interactions, and society avoids risks from unpredictable outcomes, making it essential for responsible AI deployment.
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