MIT RES.EC-001 Exploring Fairness in Machine Learning, Spring 2020
Unlock Ethical AI: Navigating Fairness and Bias in Machine Learning with MIT Experts!
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8 learners
What you'll learn
- Understand the ethical considerations in machine learning.
- Explore methods for ensuring fairness in machine learning models.
- Analyze case studies to identify and address bias in datasets.
- Apply fairness criteria to improve machine learning algorithm equity.
This course includes
- 1.3 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 9 lessons • 1.3 hours of video
Ethics and Fairness in Machine Learning: A Comprehensive Guide
9 lessons
• 1.3 hours
Ethics and Fairness in Machine Learning: A Comprehensive Guide
9 lessons
• 1.3 hours
- Introduction to Ethics in Machine Learning 01:52
- Exploring Fairness in Machine Learning: Background 05:15
- USAID Appropriate Use Framework, Exploring Fairness in Machine Learning 09:01
- Solar Lighting Example, Exploring Fairness in Machine Learning 06:20
- Fairness Criteria, Exploring Fairness in Machine Learning 07:07
- Protected Attributes and 'Fairness through Unawareness,' Exploring Fairness in Machine Learning 06:18
- Case Studies with Data: Mitigating Gender Bias on the UCI Adult Dataset 22:16
- Pulmonary Health Case Study: Bias Exploration, Exploring Fairness in Machine Learning 05:31
- Case Study: Identifying and Mitigating Unintended Demographic Bias in Machine Learning for NLP 13:03
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