Presentation: Putting Fairness Principles Into Practice
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Abstract
As more researchers have become aware of and passionate about algorithmic fairness, there has been an explosion in papers laying out new metrics, suggesting algorithms to address issues, and calling attention to issues in existing applications of machine learning. This research has greatly expanded our understanding of the concerns and challenges in deploying machine learning, but there has been much less work in seeing how the rubber meets the road. In this talk I present a case-study on the application of fairness in machine learning research to a production classification system, and offer new insights in how to measure and address algorithmic fairness issues.
2019 Tracks
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Hands-on Codelabs & Speakers Office Hours
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Papers in Production: Modern CS in the Real World
Groundbreaking papers make real-world impact.
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Hands-on Codelabs & Speakers Office Hours
Codelabs are a self-guided tutorial of a product, API, or tool kit followed by an Office Hour period with the lab’s creator.
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Solving Software Engineering Problems with Machine Learning
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Predictive Architectures in the Real World
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Predictive Data Pipelines & Architectures
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Sequential Data: Natural Language, Time Series, and Sound
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ML in Action
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Deep Learning in Practice
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