Data Governance Critical for Building Responsible Generative AI Systems
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Data governance is critical for building enterprise generative AI apps to manage new unstructured data while ensuring privacy, security, and quality policies.
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Unstructured data like documents and transcripts need to be ingested, catalogued, and linked with structured data to provide context for generative AI models.
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Data privacy policies should be implemented to treat sensitive information, with techniques like redaction, while retaining semantic context.
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Shift-left data quality mechanisms should be used to detect issues early in pipelines before they impact model accuracy and bias.
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User request-response workflows need access controls and compliance checks to enforce security, prevent exposure of sensitive data, and reduce harmful outcomes.