Category: 2019

Data Science Ethical Considerations: A Systematic Literature Review and Proposed Project Framework

Big Data, Big Data Analytics, Classification, Data Analysis

Author: Jeffrey S. Saltz, Neil Dewar; Publisher: Springer Link; Publication Year: 2019. The following article discusses how data science, and the related field of big data, is an emerging discipline involving the analysis of data…
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10 Things Judges Should Know About AI

Algorithms, Artificial Intelligence, Duke University, Judicial System, Racial Injustice

Author: Jeff Ward; Publisher: Judicature; Publication Year: 2019. The following article features Professor Jeff Ward of Duke University who discusses how artificial intelligence (AI) is being used in courtrooms. Current AI tools are effective in…
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The Danger of AI is Weirder Than You Think

Artificial Intelligence, Artificial Intelligence Development

Author: Janelle Shane; Publisher: TED; Publication Year: 2019. The following TEDx Talk explores the nature of relationships between humans and artificial intelligence (AI). Shane proposes that AI was a tool that humans (particularly data scientists)…
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What Do We Do About the Biases in AI?

Algorithms, Amazon, Artificial Intelligence, Bias Mitigation, Explainability, Fairness, Human Bias, Racial Bias, Transparency

Author: James Manyika, Jake Silberg, Brittany Presten Publisher: Harvard Business Review Publication Year: 2019 Summary: The following article discusses how artificial intelligence (AI) can help identify and reduce the impact of human biases. But it…
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Tackling Bias in Artificial Intelligence

Artificial Intelligence, Fairness, Human Bias, Racial Disparities

Author: Jake Silberg, James Manyika; Publisher: McKinsey & Company; Publication Year: 2019. The following article discusses 2 opportunities that artificial intelligence (AI) presents to today’s society: the opportunity to reduce the effect of human bias,…
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Algorithmic Bias and Fairness: Crash Course AI #18

Algorithms, Discrimination, Efficiency, Facial Recognition Systems, Manipulated Data, Training Data, Unbalanced Data

Author: Jabril Ashe; Publisher: CrashCourse; Publication Year: 2019. The following video discusses how bias is a natural outcome as systems such as the human brain or a computer algorithm try to take shortcuts in order…
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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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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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