How can we measure bias in AI evaluations?

How can we measure bias in AI evaluations?

Measuring bias in AI evaluations involves analyzing the outcomes of AI models across different demographic groups.

What metrics can we use to assess bias?

Common metrics include disparate impact, equal opportunity, and predictive parity, among others.

Can you give an example of how to apply these metrics?

Sure! For instance, if an AI model predicts loan approvals, we can compare approval rates between different racial groups.

What steps can we take to reduce bias in AI?

To reduce bias, we can use diverse training data, implement fairness constraints, and regularly audit model performance.