Data Science in Context: Foundations, Challenges, Opportunities [Hardcover]

Four leading experts convey the promise of data science and examine challenges in achieving its benefits and mitigating some harms.Four leading experts convey the excitement and promise of data science and examine the major challenges in gaining its benefits and mitigating potential harms. Aimed at practitioners and students as well as humanists, social scientists, scientists, and policy makers, the book discusses how to use data science more effectively and more ethically.Four leading experts convey the excitement and promise of data science and examine the major challenges in gaining its benefits and mitigating potential harms. Aimed at practitioners and students as well as humanists, social scientists, scientists, and policy makers, the book discusses how to use data science more effectively and more ethically.Data science is the foundation of our modern world. It underlies applications used by billions of people every day, providing new tools, forms of entertainment, economic growth, and potential solutions to difficult, complex problems. These opportunities come with significant societal consequences, raising fundamental questions about issues such as data quality, fairness, privacy, and causation. In this book, four leading experts convey the excitement and promise of data science and examine the major challenges in gaining its benefits and mitigating its harms. They offer frameworks for critically evaluating the ingredients and the ethical considerations needed to apply data science productively, illustrated by extensive application examples. The authors' far-ranging exploration of these complex issues will stimulate data science practitioners and students, as well as humanists, social scientists, scientists, and policy makers, to study and debate how data science can be used more effectively and more ethically to better our world.Introduction; Part I. Data Science: 1. Foundations of data science; 2. Data science is transdisciplinary; 3. A framework for ethicló2