How can we measure bias in AI training data?

How can we measure bias in AI training data?

Measuring bias in AI training data involves several techniques, such as statistical analysis, fairness metrics, and audits.

What are some common fairness metrics used?

Common fairness metrics include demographic parity, equal opportunity, and disparate impact, each assessing different bias aspects.

Can you explain demographic parity?

Demographic parity requires that the decision-making outcomes are independent of sensitive attributes like race or gender.

How can we mitigate bias in training data?

Mitigating bias can involve techniques like re-sampling, data augmentation, and using fairness-aware algorithms.