Why is AI model validation important?
AI model validation is crucial to ensure that models perform well on unseen data and meet desired accuracy.
What are the risks of not validating an AI model?
Without validation, models may produce inaccurate predictions, leading to poor decision-making and potential harm.
How often should AI models be validated?
AI models should be validated regularly, especially when new data is introduced or when the model's performance declines.
What techniques are used for AI model validation?
Common techniques include cross-validation, holdout validation, and performance metrics like accuracy and F1 score.
Can you give an example of a failed AI model due to lack of validation?
One notable example is the facial recognition system that misidentified individuals, leading to wrongful arrests.
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