Build the governance frameworks and risk management capabilities to deploy AI responsibly and safely
AI introduces new categories of risk that traditional frameworks don't address. From algorithmic bias to hallucinations, from regulatory exposure to reputational damage, executives must understand and manage risks unique to AI systems.
This module equips you with governance structures, risk taxonomies, and practical controls to ensure AI deployments are safe, compliant, and aligned with your organization's values.
"AI governance isn't about stopping innovation - it's about enabling responsible innovation at scale."
Master the seven categories of AI risk and learn to identify, assess, and prioritize risks across your AI portfolio.
Design AI governance frameworks including councils, policies, and oversight mechanisms appropriate for your organization.
Implement ethical AI principles covering fairness, transparency, accountability, and human oversight requirements.
Navigate the emerging AI regulatory landscape including EU AI Act, industry-specific requirements, and global frameworks.
Understand algorithmic bias sources and implement testing, monitoring, and mitigation strategies for fair AI systems.
Build AI incident response capabilities including detection, containment, and communication protocols.
Build the governance frameworks that enable innovation while managing risk appropriately.
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