How to Build an AI Governance Framework That Actually Enforces Privacy

An AI governance framework is essential for ensuring that AI systems adhere to ethical and regulatory standards throughout their lifecycle, from data training to deployment and updates. While many organizations establish governance policies, these often fail at the enforcement stage, lacking the technical controls necessary to manage AI systems in production environments. Effective AI governance requires more than principles; it necessitates infrastructure that enforces policies such as fairness, accountability, transparency, and security, using privacy-enhancing technologies and continuous risk management. Frameworks like the NIST AI RMF, EU AI Act, and ISO/IEC 42001 guide organizations in aligning AI systems with legal requirements and reducing algorithmic bias. Enforcement at the infrastructure level, rather than just policy, is crucial, involving encryption, federated learning, and secure multiparty computation to protect data and ensure compliance. Duality Technologies exemplifies this approach by integrating privacy and compliance directly into AI systems, helping organizations move from defining governance principles to enforcing them effectively.

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