Ethics & Bias in Machine Learning

Summary

Models trained on historical data can encode and amplify existing societal biases — recognizing this risk and testing for it is a core professional responsibility, not an optional add-on.

• 1Read a real case study of a biased model that caused a public issue.
• 2Learn to check model performance across different demographic subgroups, not just in aggregate.
• 3Practice identifying a potential bias risk in a hypothetical model idea of your own.