156 | Visualizing Fairness in Machine Learning with Yongsu Ahn and Alex Cabrera
Data Stories
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Is There a Difference Between Machine Learning and Human Computer Decisions?
Sooner or later, we have to go back to human decisions, right? And yet, i think that's challenge. How do you communicate these really complex trade offs between different definitions of fairness and accuracy into like, easily understandable trade offs that people can actually reason about and make ethical decisions? I think there's a very interesting space there that, i think, its just starting to be explored, that i think has really interesting implications. Also. instead of having maybe a machine learning person sitting at their computer and being like, the false positive rate, i think is more important than calveration,. 'm going to choose that they're thinking of, hay"
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