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Module 1: Introduction to Ethics in Machine Learning
Background
Module 2: Examples of Ethical Challenges in ML
USAID Appropriate Use Framework
Solar Lighting Example
Module 3: Pedagogical Framework for Addressing Ethical Challenges
Protected Attributes and Fairness through Unawareness
Fairness Criteria
Module 4: Case Studies with Data
Mitigating Gender Bias
Case Study on Pulmonary Health
Demographic Bias in NLP
Course Info
Instructors
Dr. Richard Fletcher
Prof. Daniel Frey
Dr. Mike Teodorescu
Amit Gandhi
Audace Nakeshimana
Departments
Supplemental Resources
As Taught In
Spring 2020
Level
Non Credit
Topics
Engineering
Computer Science
Artificial Intelligence
Teaching and Education
Curriculum and Teaching
Learning Resource Types
theaters
Lecture Videos
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RES.EC-001 | Spring 2020 | Non Credit
Exploring Fairness in Machine Learning for International Development
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More Info
Module 1: Introduction to Ethics in Machine Learning
Background
Module 2: Examples of Ethical Challenges in ML
USAID Appropriate Use Framework
Solar Lighting Example
Module 3: Pedagogical Framework for Addressing Ethical Challenges
Protected Attributes and Fairness through Unawareness
Fairness Criteria
Module 4: Case Studies with Data
Mitigating Gender Bias
Case Study on Pulmonary Health
Demographic Bias in NLP
Fairness Criteria
RES.EC-001 Exploring Fairness in Machine Learning, Protected Attributes and "Fairness through Unawareness"
pdf
RES.EC-001 Exploring Fairness in Machine Learning, Protected Attributes and "Fairness through Unawareness"
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Course Info
Instructors
Dr. Richard Fletcher
Prof. Daniel Frey
Dr. Mike Teodorescu
Amit Gandhi
Audace Nakeshimana
Departments
Supplemental Resources
As Taught In
Spring 2020
Level
Non Credit
Topics
Engineering
Computer Science
Artificial Intelligence
Teaching and Education
Curriculum and Teaching
Learning Resource Types
theaters
Lecture Videos
Download Course