Material Detail
Exploring Fairness in Machine Learning for International Development
In an effort to build the capacity of the students and faculty on the topics of bias and fairness in machine learning (ML) and appropriate use of ML, the MIT CITE team developed capacity-building activities and material. This material covers content through four modules that an be integrated into existing courses over a one to two week period.
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More about this material
- Material Type:
- Online Course Module
- Date Added to MERLOT:
- March 30, 2022
- Date Modified in MERLOT:
- March 30, 2022
- Author:
- Richard Fletcher, et al., MIT
- Submitter:
-
Cathy Swift
- Primary Audience:
- College Upper Division, Graduate School
- Technical Format:
- Website
- Mobile Compatibility:
- Not specified at this time
- Language:
- English
- Cost Involved:
- No
- Source Code Available:
- Unknown
- Creative Commons:
-
This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International
