Category: Education & Training

Algorithmic Bias Detection and Mitigation: Best Practices and Policies to Reduce Consumer Harms

Algorithms, Artificial Intelligence, Bias Mitigation, Human Bias, Technical Diligence

Author: Nicol Turner Lee, Paul Resnick, Genie Barton; Publisher: Brookings; Publication Year: 2019. The following piece describes how artificial intelligence (AI) is being used to manage greater aspects of our economy. There is risk that…
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The Biases We Feed to Tinder Algorithms

Algorithms, Dating Apps, Discriminatory Practices, Elo-Score, Tinder

Author: N/A; Publisher: Diggit Magazine; Publication Year: 2019. The following article discusses how algorithms play a crucial role in overall participation in public life. When it comes to apps similar to Tinder, scholars stress the…
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Ethical research: goodpractice guide toresearching LGBTcommunities and issues

Anonymity, Coercion, Confidentiality, Informed Consent, Integrity, LGBTQIA+, Voluntary Participation

Author: N/A; Publisher: LGBT Foundation; Publication Year: N/A. The following article is a guide to navigating ethics issues that can arise when performing research (specifically on members of the LGBT community). The guide is split…
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Racial Equity and Data Science

Big Data, Discriminatory Practices, Racial Discrimination, Racial Equality

Author: MIT IDSS; Publisher: MIT Political Science; Publication Year: 2022. The following article features the Research Initiative on Combating Systematic Racism (ICSR) who’s goal is to seed and coordinate research used to identify racially discriminatory…
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Fairlearn

Algorithms, Artificial Intelligence, Fairlearn, Fairness, Unfairness Mitigation

Author: Miro Dudik; Publisher: Fairlearn; Publication Year: N/A. The following tool is Fairlearn which is a open-source project that helps data scientists improve fairness of their artificial intelligence (AI) systems. It includes a python library…
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Ethics and Data Science

Consent, Consequences, Control, Data Collection, Data Interpretation, Data Modeling, Guidelines, Model Implementation

Author: Mike Loukides, Hilary Mason, DJ Patil; Publisher: O’Reilly; Publication Year: 2018. The following book focuses on implementing ethical guidelines into data scientists’ daily work. The authors provide 5 framing guidelines: consent, clarity, consistency, control,…
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Lies, Racism and Sexism: The Power of Data Stories

Algorithms, Artificial Intelligence, Blind Faith, Facial Recognition Systems, Storytelling

Author: Mike Bugembe; Publisher: TED; Publication Year: N/A. The following talk discusses how algorithms inherently have bias and there is a common problem of blind faith in data. Blind faith in data is trusting whatever…
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3 Ways to Reduce Implicit Bias in Predictive Analytics for Better Health Equity

Artificial Intelligence, Implicit Bias

Author: Michael A. Simon; Publisher: Drug: Discovery & Development; Publication Year: 2022. The following article first explains how implicit bias is present in the medical setting, and then links this train of thought into how…
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The Evolution of Data Ethics in Clinical Research and Drug Development

Advanced Analytic Techniques, Biometric Data, Clinical Research, Data Sourcing, Drug Development, Real World Data

Author: Melissa Heidelberg; Publisher: Ethics, Medicine and Public Health; Publication Year: 2020. The following article discusses how the usage of advanced analytic techniques has revolutionized countless industries, and the clinical research and drug development industry…
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