How can we mitigate bias in AI systems?

How can we mitigate bias in AI systems?

There are several techniques to mitigate bias in AI systems, such as data preprocessing, algorithmic adjustments, and regular audits.

Can you explain data preprocessing?

Data preprocessing involves cleaning and transforming data to ensure it is representative and free from biases before training.

What are some algorithmic adjustments?

Algorithmic adjustments can include using fairness constraints, re-weighting training samples, or employing adversarial debiasing.

How often should we conduct audits?

Audits should be conducted regularly, ideally after major updates or changes to the model, to ensure ongoing fairness.