156 | Visualizing Fairness in Machine Learning with Yongsu Ahn and Alex Cabrera
Data Stories
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Machine Learning and Fairness in Machine Learning Problems
Young: There hasn't been much work on this fairness in machine learning problem. So we kind of wanted to propose a mind map of how decision makers can look at the problem for the purpose of the fairness combating bias. We support measuring the biases to quantify and make it comparable. And then we also support identifying the biass in each feature and to mitigate the bias.
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