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Creators/Authors contains: "Johnson, Brittany"

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  1. ; ; ; ; ; (, EURO Journal on Decision Processes)
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  2. ; (, Proceedings of the Demonstrations Track at the 44th International Conference on Software Engineering (ICSE))
    Advances in how we build and use software, specifically the integration of machine learning for decision making, have led to widespread concern around model and software fairness. We present fairkit-learn, an interactive Python toolkit designed to support data scientists' ability to reason about and understand model fairness. We outline how fairkit-learn can support model training, evaluation, and comparison and describe the potential benefit that comes with using fairkit-learn in comparison to the state-of-the-art. Fairkit-learn is open source at https://go.gmu.edu/fairkit-learn/. 
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  3. ; ; ; (, Forest Ecology and Management)
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  4. ; ; (, Proceedings of the 42nd International Conference on Software Engineering (ICSE))
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  5. ; ; ; (, Proceedings of the Demonstrations Track at the 26th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE))
    Bias in decisions made by modern software is becoming a common and serious problem. We present Themis, an automated test suite generator to measure two types of discrimination, including causal relationships between sensitive inputs and program behavior. We explain how Themis can measure discrimination and aid its debugging, describe a set of optimizations Themis uses to reduce test suite size, and demonstrate Themis' effectiveness on open-source software. Themis is open-source and all our evaluation data are available at http://fairness.cs.umass.edu/. See a video of Themis in action: https://youtu.be/brB8wkaUesY 
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