Assignment #1: Bias Detection and Analysis
Due Date: 23:59
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In this assignment, you will explore bias in real-world datasets and machine learning models. You will:
- Data Analysis: Analyze a provided dataset for potential sources of bias
- Bias Detection: Implement methods to detect different types of bias in the data
- Fairness Metrics: Calculate various fairness metrics (demographic parity, equalized odds, etc.)
- Mitigation Strategies: Apply and evaluate bias mitigation techniques
- Report: Write a report documenting your findings and recommendations
Learning Objectives:
- Identify sources of bias in datasets
- Compute and interpret fairness metrics
- Apply bias mitigation techniques
- Critically evaluate trade-offs between fairness and performance
Deliverables:
- Python notebook with your analysis and code
- Written report (4-6 pages)
- Reflection on ethical implications
Resources: