WEBVTT

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Defining AI data provenance risks

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Internet scraping, copyright, and regulation pressure

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Audit trails meet non-deterministic AI models

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AI supply chain and missing “bill of materials”

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Compliance, quality, and security consequences

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Building governance in AI systems

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Practical first steps: catalogs and tracing

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Executive priorities and avoiding snake oil

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Beyond point fixes: prompt injection and resilience

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Risk-based approach and community resources