Category: Social Justice
-
The Danger of AI is Weirder Than You Think
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)…
-
AI can be Sexist and Racist — It’s Time to Make it Fair
Accuracy, Algorithms, Artificial Intelligence, Cultural Bias, Ethnic Bias, Gender Bias, Training DataAuthor: James Zou, Londa Schiebinger; Publisher: Nature; Publication Year: 2018. The following article discusses different sources of bias, how to recognize the bias, and what to do about it. They bring up that a major…
-
How Can Data Science Fight Social Injustice?
Author: James Nelson; Publisher: Medium; Publication Year: 2020. The following article delves into the divide between law enforcement and the communities that they are entrusted with protecting, and suggests that data science is a possible…
-
Data Science for Social Good with Datakind’s Jake Porway
Author: Jake Porway; Publisher: O’Reilly Media; Publication Year: 2015. The following video discusses how data for good is becoming very popular, but many people are not thinking deeply about ethics as they do it, and…
-
Ethical OS: A Guide to Anticipating the Future Impact of Today’s Technology
Author: N/A; Publisher: Tech and Society Solutions Lab; Publication Year: 2018. The following guide anticipates the long-term social impact and unexpected uses of the tech created today. This guide is to help creators anticipate risks…
-
Health Data Poverty: An Assailable Barrier to Equitable Digital Health Care
Data Collection, Data Privacy, Equity Gap, Health Data, Health Data Poverty, Healthcare Inequality, Healthcare Services, Machine Learning, Representation, TransparencyAuthor: Hussein Ibrahim, Xiaoxuan Liu, Nevine Zariffa, Andrew D. Morris, Alastair K. Denniston; Publisher: The Lancet Digital Health; Publication Year: 2021. The following study identifies how machine learning and advanced technologies can now be used…
-
FAIR Principles
Accessibility, Fairness, Findability, GO FAIR, Implementation Networks, Interoperability, ReusabilityAuthor: N/A; Publisher: GO FAIR; Publication Year: 2016. The following article focusses on GO FAIR, a stakeholder-driven and self-governed initiative that aims to implement the FAIR data principles. They use Implementation Networks to define and…
-
The Racial Data Gap: Lack of Racial Data as a Barrier to Overcoming Structural Racism
Author: Geoffrey Holtzman, Neda Khoshkhoo, Elaine Nsoesie; Publisher: The American Journal of Bioethics; Publication Year: 2022. The following article discusses how there is a consistent racial disparity in data, particularly as this article points out,…
-
Ethics in Natural Language Processing
Aggregation Bias, Deployment Bias, Evaluation Bias, Learning Bias, Natural Language Processing Technology, SlangAuthor: Future Analytica; Publisher: Medium; Publication Year: 2022. The following article discusses data ethics in context of natural language processing. Several types of bias that we need to watch out for are learning bias, evaluation…