Resources | Exploring Fairness in Machine Learning for International Development | Edgerton Center | MIT OpenCourseWare

Download

Download course

This package contains the same content as the online version of the course, except for the audio/video materials, which can be downloaded using the links below. Once downloaded, follow the steps below. For more help using these materials, read our FAQs.

To open the homepage, click on the index.html file.
To find the course resource files such as PDFs, open the static_resources folder.

Note: The downloaded course may not work on mobile devices. We recommend using a computer with the downloaded course package.

Lecture Videos

Case Studies with Data: Mitigating Gender Bias on the UCI Adult Dataset

Case Study: Identifying and Mitigating Unintended Demographic Bias in Machine Learning for NLP

Exploring Fairness in Machine Learning: Background

Fairness Criteria, Exploring Fairness in Machine Learning

Introduction to Ethics in Machine Learning

Protected Attributes and "Fairness through Unawareness," Exploring Fairness in Machine Learning

Pulmonary Health Case Study: Bias Exploration, Exploring Fairness in Machine Learning

Solar Lighting Example, Exploring Fairness in Machine Learning

USAID Appropriate Use Framework, Exploring Fairness in Machine Learning

Course Info

Instructors

Departments

Edgerton Center

As Taught In

Spring 2020

Level

Non-Credit

Topics

Learning Resource Types

Lecture Videos

Download Course

MIT Open Learning

Over 2,500 courses & materials

Freely sharing knowledge with learners and educators around the world. Learn more

© 2001–2026 Massachusetts Institute of Technology

Accessibility

Creative Commons License

Terms and Conditions

Proud member of:

© 2001–2026 Massachusetts Institute of Technology