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Why the World Needs More Women Data Scientists
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Author: Ugonma Nwankwo, Michael Pisa; Publisher: Center for Global Development; Publication Year: 2021. The following article discusses how evidence-based policy making is ineffective when it relies on biased information, a potential source for this is bias in the datasets. In the U.S., women make up 18% of data scientist jobs and in lower-income countries, that…
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Keynote Speaker: Joy Buolamwini Presented by SpeakInc
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Author: Joy Buolamwini Publisher: SpeakInc Publication Year: 2018 Summary: In the following video, Joy Buolamwini expands on her mission of the ‘Coded Gaze’, her term for algorithmic bias which can lead to discriminatory practices or exclusionary experiences. She recalls her experience of her face only being recognized after she wore a white mask. She provides…
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We Don’t Have Enough Women in Clinical Trials — Why That’s a Problem
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Author: Elizabeth Pratt; Publisher: Healthline; Publication Year: 2020. The following article discusses how data scientists need to be cautious about applying results across all demographics if all demographics were not well represented in the data used to train the model. Our pharmaceutical industry relies on measurements and samples taken during drug trials to set dosing…
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Why We Must Act Now to Close the Gender Gap in AI
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Author: Gabriela I. Ramos Patiño; Publisher: World Economic Forum; Publication Year: 2022. The following article provides nicely linked research studies – and it is a quick high-level read but highlights an important issue in artificial intelligence (AI) development and the gender gap that is just as important as race inclusion. Women make up only 22%…
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Incorporate Inclusivity
Author: Data Science Ethics Podcast Publisher: Spotify Publication Year: 2020 Summary: The following podcast episode discusses how gender and racial gaps exist in the field of data science as it tends to be dominated by certain groups such as white men. While we understand that inclusivity and diversity are essential for ethical data science practices,…
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Data Feminism Presents an Intersectional Feminist Way to Think About Data Science and Ethics
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Author: Catherine D’Ignazio and Lauren Klein; Publisher: Ms. Magazine; Publication Year: 2020. The following article discusses how the dominant group of data scientists today are straight, white, cisgender man who has formal credentials and is from the United States. The world was designed for him and he may not think about how the world may…
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Invisible Women
Author: Caroline Criado Perez; Publisher: Vintage Books; Publication Year: 2020. The following book shows us how bias exists in even the most innocuous of circumstances. In systems that are primarily designed for and by men, many systematically ignore the female half of the population. Criado Perez provides case studies from nearly every sect to showcase…
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We Need to Close the Gender Data Gap By Including Women in Our Algorithms
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Author: Caroline Criado Perez; Publisher: Time Magazine; Publication Year: 2020. The following article describes the way that so many aspects of our society is designed with men in mind instead of women. Examples of this include the fact that cars are 71% less safe for women because they are tested using make crash dummies, or…
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AI Bias Could Put Women’s Lives At Risk – A Challenge For Regulators
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Author: Carmen Neithammer; Publisher: Forbes; Publication Year: 2020. The following article touches on the bias that is introduced into algorithms by using data sets that are comprised mainly of information about the male population. A paper released for the European Union on the regulation of artificial intelligence includes requirements for algorithm builders to act against…
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