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: 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…
Author: James M. Connolly; Publisher: Information Week; Publication Year: 2022. The following article is a great, comprehensive description of artificial intelligence (AI) ethics and bias with a lot of supporting articles linked throughout. It begins…
Author: James Kobielus; Publisher: Transforming Data with Intelligence (TDWI); Publication Year: 2021. The following article focuses on why there are ethical boundaries needed when building robotic assistants in this article. Developers of the artificial intelligence…
Author: James Hodson, Jon Krohn; Publisher: Super Data Science; Publication Year: 2021. The following podcast episode is an interview with James Hodson who founded AI for Good. He started the organization to focus on using…
Author: James Bessen, Stephen Michael Impink, Robert Seamans; Publisher: The Center on Regulation and Markets at Brookings; Publication Year: 2022. The following paper discusses an academic approach to researching and quantifying artificial intelligence ethic progress…
Author: James Arvanitakis, Andrew Francis, Oliver Obst; Publisher: The Conversation; Publication Year: 2018. The following article discusses how, as analysts, the main 2 ethical questions that are being asked are 1). What data should be…
Author: Jakub Wisniewski, Przemyslaw Biecek; Publisher: The R Journal; Publication Year: 2022. The following article discusses how as more sophisticated machine learning methods become more ubiquitous, a culture of classifying between “explainable” and “unexplainable” models…
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,…