Ethical Data Science: Prediction in the Public Interest

Data science can serve the public interest by providing a solution-oriented approach to the ethical challenges of data science. Ethical Data Science empowers those striving to create predictive data technologies that benefit more people, highlighting moral questions alongside the interlocking legal and commercial interests influencing data science. It encourages readers to think critically about the full human potential of data science and calls for more inclusive data science.

Format: Hardback
Length: 176 pages
Publication date: 23 January 2024
Publisher: Oxford University Press Inc

Data science has the potential to serve the public interest, but scientific solutions to social problems often face challenges. Predictions in data science are often seen as a technocratic tool that prioritizes financial interests over the well-being of humanity. However, Anne L. Washington offers a solution-oriented approach to the ethical challenges of data science in her book, Ethical Data Science. This book empowers individuals and organizations working on developing predictive data technologies that prioritize the well-being of more people. As one of the first books on public interest technology, Ethical Data Science provides a starting point for anyone who wants to counterbalance institutional incentives that drive computational prediction.

The book argues that data science predictions often embed administrative preferences that overlook the marginalized and disenfranchised. It introduces the concept of the prediction supply chain to highlight moral questions alongside the legal and commercial interests influencing data science. The book is structured around a typical data science workflow and systematically outlines the potential for more nuanced approaches to transforming data into meaningful patterns. By drawing on arts and humanities methods, the book encourages readers to think critically about the full human potential of data science step-by-step.

Situating data science within multiple layers of effort exposes dependencies and provides opportunities for research ethics and policy interventions. This approachable process lays the foundation for broader conversations with a wide range of audiences, including practitioners, academics, students, policy makers, and legislators. By learning how to identify social dynamics in data trends and reflect on ethical considerations, these audiences can contribute to the development of data science that serves the public interest.

Weight: 404g
Dimension: 162 x 243 x 20 (mm)
ISBN-13: 9780197693025