Summary • Syllabus • Student Showcase • Resources
MORPH is a free, intensive online enrichment opportunity for high school students started by undergrad students amidst high schoolers' summer program cancellations due to COVID-19. Students will explore topics in mathematics, statistics, and computer science that are rarely studied in high school, and will build learning skills that are valuable across disciplines. This 8-week summer course was taught as part of the program.
Fair Bytes is a partnering organization advancing AI fairness & ethics education, currently expanding its plans and programming.
When computer & machine learning algorithms are applied to humans, we’ve found that there are unintended, unfair consequences. There is a growing awareness that decisions we make about our data, methods, and tools are often tied up with their impact on people and societies. Algorithmic fairness is a field that explores how to quantify fairness and bias of algorithms for individuals and groups and how to use these mathematical underpinnings to mitigate bias.
This course introduces high school students to theory and real-world applications of algorithms and artificial intelligence (AI), as well as the potential ethical implications associated with them. We discuss the field of fairness from both technical and ethical perspectives.
Week | Date | Theme | Topics | Assignments | Slides |
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0 | Preparation |
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1 | 6/19 | Introduction |
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2 | 6/26 | Fairness in Classification |
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3 | 7/3 | Causality and Counterfactuals |
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4 | 7/10 | Applying Fairness to Algorithms I |
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5 | 7/17 | Applying Fairness to Algorithms II |
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6 | 7/24 | Applying Fairness to Algorithms III |
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7 | 8/2 | Guest Lecture: Implementing Machine Learning |
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8 | 8/7 | Course Wrap-Up |
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