Category: Education & Training

Erasing Bias in Emerging Technologies – 3 Considerations

Data Collection, Generalizability, Race-Based Models

Author: Ivor Horn, Kulleni Gebreyes; Publisher: World Economic Forum; Publication Year: 2022. In the following article, 2 healthcare industry professionals walk through 3 considerations all providers should make. The first big pitfall most providers fall…
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Invisible Women: Exposing Data Bias in a World Designed for Men – a Review

Data Bias, Gender Bias, Gender Norms, Gender Roles

Author: Karen Boyle; Publisher: The Conversation; Publication Year: 2019. The following article reviews the book “Invisible Women, Exposing Data Bias in a World Designed for Men” by Caroline Criado Perez. The book reveals some truths…
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Handle with Care: Lessons for Data Science from Black Female Scholars

Algorithms, Black Women, Data Collection, Defaults, Discrimination, Racism, Stereotypes

Author: Inioluwa Deborah Raji; Publisher: Patterns; Publication Year: 2020. The following article begins by confronting the idea that data science aims to reduce people to one dimensional ideas or stereotypes. When individuals or organizations attempt…
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Data Ethics: What It Is and Why It’s Important

Customer Data, Data Collection, Data Ownership, Data Usage, Private Data

Author: impacX team; Publisher: impacX; Publication Year: N/A. The following article describes how data ethics is an extremely important aspect of how a company should approach its collection and use of data. However, as data…
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Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them

Debiasing, Gender Bias, Natural Language Processing Technology, Word Embeddings

Author: Hila Gonen, Yoav Goldberg; Publisher: Allen Institute for Artificial Intelligence; Publication Year: 2019. The following study talks about gender bias in word embeddings, an important component in Natural Language Processing. There have been debiasing…
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The Problem with “Biased Data”

Machine Learning, Mental Framework, Terminology & Language

Author: Harini Suresh; Publisher: Medium; Publication Year: 2019. In the following article, the author points out that language matters and that the right terminology forms a mental framework. The author also provides a framework for…
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Data Science Ethics

Algorithmic Fairness, Anonymity, Consent, Data Ownership, Data Validity, University of Michigan

Author: H.V. Jagadish; Publisher: University of Michigan, Coursera; Publication Year: N/A. The following course from the University of Michigan on Coursera. It is primarily an introductory course that provides the history of the concept of…
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Why Data Scientists Should Make a Commitment to Diversity

Algorithms, Fairness

Author: N/A; Publisher: Information Week; Publication Year: 2018. The following article emphasizes the power that data scientists hold when addressing ethics, as many big companies employ them to create impactful algorithms and recommendations. Specifically, data…
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Truth in Pictures: What Google Image Searches Tell Us About Inequality at Work

Gender Bias, Google, Racial Bias, Representation, Search Engine

Author: Gretchen Hellman; Publisher: Diversity Employers; Publication Year: 2017. The following article speaks about the bias of search engines. If you were to look for images of a “professor” or “CEO” you would find images…
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