What are the best practices for evaluating AI systems?

What are the best practices for evaluating AI systems?

The best practices include defining clear evaluation metrics, using diverse datasets, and conducting regular audits.

Can you explain why diverse datasets are important?

Diverse datasets help ensure that the AI performs well across different demographics and scenarios, reducing bias.

What metrics should I consider for evaluation?

Key metrics include accuracy, precision, recall, F1 score, and user satisfaction, depending on the application.

How often should AI systems be evaluated?

AI systems should be evaluated regularly, especially after significant updates or changes in data.