Explore our collection of data ethics resources
Dive into our expansive collection of articles, case studies, datasets, and multimedia content, carefully compiled and continually updated to reflect the latest in ethical considerations in analytics.
Dive into our expansive collection of articles, case studies, datasets, and multimedia content, carefully compiled and continually updated to reflect the latest in ethical considerations in analytics.
Author: Cathy O’Neil; Publisher: Crown; Publication Year: 2016. The following book discusses “weapons of math destruction”: algorithms that try to quantify subjective qualities or judgment metrics. For example, an algorithm that tries to quantify “creditworthiness”…
Author: Cathy O’Neil; Publisher: TED Talks; Publication Year: 2017. The following video highlights the dangers of blind trust in algorithmic models. O’Neil suggests that algorithms are much less scientific and objectively truthful than commonly perceived.…
Author: Cathy O’Neil; Publisher: Slate; Publication Year: 2016. The following article discusses when deciding which variables to include in a model, some factors (race, etc.) can be easily excluded to ensure that racial bias in…
Author: Catherine Thorbecke; Publisher: CNN; Publication Year: 2022. Summary: In the following article, Thorbecke informs the public of how the Iranian government has censored the Iranian people by cutting off their access to wifi in…
Author: Catherine D’Ignazio and Lauren Klein; Publisher: MIT Press; Publication Year: 2020. In the following book D’Ignazio and Klein present a new lens for thinking about data science and ethics. Their ideas are based on…
Author: Catherine D’Ignazio and Lauren Klein; Publisher: MIT Press; Publication Year: 2020. The following book chapter considers how within data science, practitioners are used to seeing the world in 1s and 0s – in fact,…
Author: Catherine D’Ignazio and Lauren Klein; Publisher: MIT Press; Publication Year: 2020. The following book chapter discusses how context is everything. Numbers are just numbers and cannot speak for themselves. Future data scientists need to…
Author: Catherine D’Ignazio and Lauren Klein Publisher: MIT Press Publication Year: 2020 Summary: The following book chapter from “Data Feminism” can be beautifully summed up by words from Black feminist sociologist Patricia Hill Collins: “Neither…
Author: Catherine D’Ignazio and Lauren Klein; Publisher: Ms. Magazine; Publication Year: 2020. The following article discusses how the dominant group of data scientists today are straight, white, cisgender man who has formal credentials and is…