Show Notes on Encode Equity Organizations have flocked to data science as a means of achieving unbiased results in decision-making on the premise that “the data doesn’t lie.” Yet, as data is reflective of the biases in our culture, in our history, and in our perspectives, it is particularly naïve to assume that models will […]
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Show Notes on Incorporate Inclusivity Data scientists develop algorithms that have broad reach across the population. Chances are that the data science team building these widely-impactful models are not, themselves, large enough to represent so big a swath of the population. How can a small, likely less-diverse team acquire the wisdom of many? In this […]
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