Description
Book SynopsisCan data science truly serve the public interest? Data-driven analysis shapes many interpersonal, consumer, and cultural experiences yet scientific solutions to social problems routinely stumble. All too often, predictions remain solely a technocratic instrument that sets financial interests against service to humanity. Amidst a growing movement to use science for positive change, Anne L. Washington offers 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. As one of the first books on public interest technology, it provides a starting point for anyone who wants human values to counterbalance the institutional incentives that drive computational prediction. It argues that data science prediction embeds administrative preferences that often ignore the disenfranchised. The book introduces the prediction supply chain to highlight moral questions alongside the i
Table of ContentsIntroduction: Ethical data science Prologue: Tracking ethics in a prediction supply chain 1: SOURCE - Data are people too 2: MODEL - Dear validity: Advice for wayward algorithms 3: COMPARE - Category hacking 4: OPTIMIZE - Data science reasoning 5: LEARN - For good 6: Show us your work or someone gets hurt 7: Prediction in the public interest References Index
