Category: 2020
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Incorporate Inclusivity – Data Science Ethics Podcast
Author: Marie Weber, Lexy Kassan; Publisher: Data Science Ethics; Publication Year: 2020. The following podcast episode discusses making sure that minorities are represented in the process of both building and testing especially if the results…
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Why Ethical Use of Data is So Important to Enterprises
Author: Maria Korolov; Publisher: TechTarget; Publication Year: 2020. The following article describes why there is an increasing demand from consumers to stop having so much of their data collected and used by companies; even employees…
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What the Data Say About Police Brutality and Racial Bias — and Which Reforms Might Work
Author: Lynne Peeples; Publisher: Nature; Publication Year: 2020. The following article discusses how with recent police brutality acts, many have been fighting for the past years on the need for better data on the force…
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Diversity in Data Science: A Systemic Inequality
Author: Luciano Vilas Boas; Publisher: Medium; Publication Year: 2020. The following article serves as a comprehensive look into why data science educators and large tech companies both do not hire at the proportion of Blacks,…
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“Ethics When You Least Expect It”: A Modular Approach
CODATARDA Schools for Research Data Science, Curriculum Development, Data Ethics Teaching, Data Science CitizenshipAuthor: Louise Bezuidenhout, Robert Quick, Hugh Shanahan; Publisher: Science and Engineering Ethics; Publication Year: 2020. The following article discusses how institutions and organizations around the world are developing research data science curricula to teach the…
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AI Usage in Banking is Forcing the Conversation around the Ethical Use of Data
Anti-Money Laundering, Artificial Intelligence, Data Control, Data Misuse, Know-Your-Customer Regulatory Checks, Payment Fraud, UnderwritingAuthor: Lisa Shields; Publisher: Inside BIG DATA; Publication Year: 2020. The following article talks about how over the past few years, the financial services industry has made huge strides in adopting new technologies like artificial…
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Bias in Machine Learning Examples: Policing, Banking, COVID-19
Author: Lisa Morgan; Publisher: Tech Target; Publication Year: 2020. The following article discusses how human bias, missing data, data selection, data confirmation, hidden variables and unexpected crises can contribute to distorted machine learning models, outcomes…