Ethics and Fairness in Machine Learning: A Comprehensive Guide
Unlock Ethical AI: Navigating Fairness and Bias in Machine Learning with MIT Experts!
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92 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
▶
Introduction to Ethics in Machine Learning01:52
Exploring Fairness in Machine Learning: Background05:14
USAID Appropriate Use Framework, Exploring Fairness in Machine Learning09:00
Solar Lighting Example, Exploring Fairness in Machine Learning06:20
Fairness Criteria, Exploring Fairness in Machine Learning07:07
Protected Attributes and 'Fairness through Unawareness,' Exploring Fairness in Machine Learning06:18
Case Studies with Data: Mitigating Gender Bias on the UCI Adult Dataset22:15
Pulmonary Health Case Study: Bias Exploration, Exploring Fairness in Machine Learning05:30
Case Study: Identifying and Mitigating Unintended Demographic Bias in Machine Learning for NLP13:03
