How can I audit AI training data?

What steps should I take to audit AI training data?

To audit AI training data, start by defining your objectives, then assess data quality, diversity, and relevance.

How do I check for bias in the training data?

You can check for bias by analyzing the data distribution, looking for underrepresented groups, and testing model outputs.

What tools can I use for auditing AI training data?

Some popular tools include TensorFlow Data Validation, IBM Watson OpenScale, and Fairness Indicators.

How often should I audit my AI training data?

It's recommended to audit your training data regularly, especially when new data is added or when model performance declines.