Computer Science · Machine Learning
A team of computer science students is developing a Machine Learning model for micro-loan approval using a training dataset that exhibits demographic imbalances. Which of the following pedagogical practices best supports the students' advanced, application-based understanding of ethical ML deployment?
Verified Solution4 OptionsUpdated: October 2026👁️1 View
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- 1Memorizing standard definitions of fairness and listing bias mitigation techniques
- 2Identifying dataset biases using metrics like Disparate Impact Ratio, experimenting with mitigation strategies, and justifying performance-fairness trade-offs✓
- 3Copying and running pre-existing bias-handling code examples from published research papers
- 4Discussing ethical algorithms theoretically without implementing, measuring, or testing bias on datasets
Correct answer
Identifying dataset biases using metrics like Disparate Impact Ratio, experimenting with mitigation strategies, and justifying performance-fairness trade-offs
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