Category: Diversity, Equity & Inclusion

WiDS podcast Episode 28, Karen Hao, Covering AI and Ethics Washing in the Tech Industry

Algorithms, Artificial Intelligence, Ethics Washing, Facebook, Misinformation, Silicon Valley

Author: Margo Gerritsen, Karen Hao; Publisher: Women in Data Science Podcast; Publication Year: N/A. In the following podcast episode, the focus is on Karen Hao who wrote an influential article in MIT Technology Review describing…
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Ethics and Empathy in Using Imputation to Disaggregate Data for Racial Equity

Academic Internal Review Boards, Accountability, Data Collection, Data Disaggregation, Imputation

Author: K. Steven Brown, LesLeigh Ford, Shena Ashley; Publisher: Racial Equity Analytics Lab; Publication Year: 2021. The following guide by the Urban Institute is meant to guide the practice of data disaggregation when using imputation,…
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Industry Best Practices for AI Governance

Machine Learning, Marginalized Groups, Materiality

Author: Joy Looney; Publisher: Data Iku; Publication Year: 2022. The following article lays out a framework for the ethical development of machine learning models. This framework contains concrete examples of actions that data scientists and…
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Artificial Intelligence Has a Problem With Gender and Racial Bias. Here’s How to Solve It

Amazon, Artificial Intelligence, Discrimination, Facial Analysis Software, Gender Bias, IBM, Microsoft, Racial Bias, Safe Face Pledge

Author: Joy Buolamwini; Publisher: Time Magazine; Publication Year: 2019. In the following article, notable data ethics advocate Joy Buolamwini shares her journey combating gender and racial bias in artificial intelligence (AI). After encountering biased facial…
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The Algorithmic Justice League

Accountable AI, AI Bias, AI Harm, Artificial Intelligence, Awareness, Equitable AI

Author: Joy Buolamwini; Publisher: The Algorithmic Justice League; Publication Year: N/A. The following group is an organization that addresses the social implications and harms of artificial intelligence (AI) by raising public awareness about the impacts…
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The Ethics of Data and of Data Science: An Economist’s Perspective

Codification, Endogeneity

Author: Jonathan Cave Publisher: The Royal Society Publication Year: 2016 Summary: The following abstract provides a practical approach to articulating main inherent data ethics components that is helpful in breaking down memorable takeaways. Specifically one…
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Inherent Trade-Offs in the Fair Determination of Risk Scores

Credit Score, Fairness, Risk Scoring

Author: Jon Kleinberg, Sendhil Mullainathan, Manish Raghavan; Publisher: N/A; Publication Year: 2016. The following publication discusses issues around risk scoring with credit scores and attempts to define “fairness” in this context. The main idea of…
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The Role of the Arts and Humanities in Thinking About Artificial Intelligence (AI)

Artificial Intelligence, Humanities, Philosophy

Author: John Tasioulas; Publisher: Ada Lovelace Institute; Publication Year: 2021. The following article takes a somewhat antagonistic view against the use of artificial intelligence (AI) and the author aims to persuade how the arts and…
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What You Need to Know About AI Ethics

Accountability, Artificial Intelligence, Data Handling, Design Choices, Explainability, Fairness, Human Oversight, Safety, Security, System Capabilities, Transparency

Author: John Edwards; Publisher: Information Week; Publication Year: 2022. The following article discusses how artificial Intelligence (AI) is becoming more popular as tech continues to grow, but with that, the number and intensity of concerns…
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