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Best Practices for Data Input Controls and Audits in AI System Training
Exploring the significance of controlling and auditing data for training AI systems to reduce risks and improve prediction accuracy. The chapter emphasizes responsible data collection, input data auditing for potential risks, implementing risk mitigations, and inviting external scrutiny for ensuring AI systems are not trained on poor quality data.