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Our Data Ethics: Measure What Matters and Don’t Be Creepy
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Author: Lauren Peate; Publisher: Multitudes; Publication Year: 2021. The following article and video discuss how when starting a new company that uses lots of user data, it is important to have a good set of principles to follow in regards to data ethics. At Multitudes, there are 5 main principles to be considered: 1). Autonomy:…
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Data Feminism
2020, Book, Code of Ethics, Communities of Practice, Diversity, Equity & Inclusion, Education & Training, Legal & Policylnbressa
Author: Catherine D’Ignazio and Lauren Klein; Publisher: MIT Press; Publication Year: 2020. In the following book D’Ignazio and Klein present a new lens for thinking about data science and ethics. Their ideas are based on the concept of “intersectionality” coined by Professor Kimberlé Crenshaw which is understood as “the acknowledgement that everyone has their own…
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The Numbers Don’t Speak for Themselves
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Author: Catherine D’Ignazio and Lauren Klein; Publisher: MIT Press; Publication Year: 2020. The following book chapter discusses how context is everything. Numbers are just numbers and cannot speak for themselves. Future data scientists need to incorporate the context with whatever models that they build because this fosters understanding the environment where the data was collected…
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On Rational, Scientific, Objective Viewpoints from Mythical, Imaginary, Impossible Standpoints
lnbressa
Author: Catherine D’Ignazio and Lauren Klein Publisher: MIT Press Publication Year: 2020 Summary: The following book chapter from “Data Feminism” can be beautifully summed up by words from Black feminist sociologist Patricia Hill Collins: “Neither ethics nor emotions are subordinated to reason.” We need to fight the patriarchal idea that emotions are bad, and that…
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