From the course: AI Governance for Organizations: Applying ISO/IEC 38507:2022

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AI governance of data use (Clause 6.4)

AI governance of data use (Clause 6.4)

From the course: AI Governance for Organizations: Applying ISO/IEC 38507:2022

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AI governance of data use (Clause 6.4)

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- [Instructor] If AI were a vehicle, then machine learning would be the engine, and the fuel would be data. The variety, volume and velocity of data needed for AI training depend on the AI use case under consideration. Training a system to recognize a fraudulent transaction may mean feeding it data from legitimate transactions that contain sensitive attributes of personally identifiable information. The organization therefore needs to have a documented path for how it acquires, uses, stores, and disposes of that data in compliance with the laws and regulations of the locations where it does business. Enshrining this concern in a policy would be a key way to document showing due care in an organization's regard for data governance. Procedures should be documented for data collection and data preparation, which can include annotation, labeling, cleaning, enriching, and aggregation, and can reflect detailed steps to control data governance. By examining biases and determining the quality…

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