Safeguard Controls

Safeguard controls are protective measures and processes that organizations put in place to prevent, detect, or respond to risks in their AI systems and data. These include technical tools like access restrictions and encryption, procedural steps like review workflows and audit trails, and governance structures like role-based permissions that limit who can modify models or datasets. For compliance officers and risk managers, effective safeguard controls are essential to demonstrating that your organization has taken reasonable steps to protect AI systems from unauthorized use, data breaches, model tampering, and other harms that could trigger regulatory penalties or liability.

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