Johns Hopkins University
Exploring Algorithmic Bias as a Policy Issue: A Teach-Out
Johns Hopkins University

Exploring Algorithmic Bias as a Policy Issue: A Teach-Out

Taught in English


Gain insight into a topic and learn the fundamentals

Ian Moura
Shannon Frattaroli, PhD, MPH

Instructors: Ian Moura

9 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace

Details to know


1 quiz

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There are 5 modules in this course

Welcome to the course & Orientation

What's included

2 readings

This module provides a definition of what algorithms are and how they are used, particularly within the context of specific policies and policy-related areas. It also invites learners to think about the ways algorithms are being integrated into their own area of focus.

What's included

11 videos11 readings1 quiz1 discussion prompt

This module explains what it means for an algorithm to be biased and discusses potential sources of bias within an algorithm. Learners will also have the opportunity to think through the ways that specific choices about outcomes and measurement often facilitate algorithmic bias.

What's included

11 videos7 readings1 discussion prompt

This module explores the connections between algorithmic bias and other forms of systemic discrimination. Learners will also explore the ways that choices about using algorithms often reflect societal power and inequality.

What's included

13 videos4 readings1 discussion prompt

This final module will highlight specific steps that can help reduce the risk and impact of algorithmic bias on people and communities. Learners will also identify others with whom they can share what they have learned about the ways algorithms may perpetuate and heighten existing disparities.

What's included

13 videos10 readings3 discussion prompts


Ian Moura
Johns Hopkins University
1 Course602 learners
Shannon Frattaroli, PhD, MPH
Johns Hopkins University
7 Courses9,768 learners

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