{"product_id":"humancentered-data-science-isbn-9780262543217","title":"Human-Centered Data Science","description":"\u003cb\u003eBest practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets.\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eHuman-centered data science is a new interdisciplinary field that draws from human-computer interaction, social science, statistics, and computational techniques. This book, written by founders of the field, introduces best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of very large datasets. It offers a brief and accessible overview of many common statistical and algorithmic data science techniques, explains human-centered approaches to data science problems, and presents practical guidelines and real-world case studies to help readers apply these methods.\u003cbr\u003e \u003cbr\u003eThe authors explain how data scientists’ choices are involved at every stage of the data science workflow—and show how a human-centered approach can enhance each one, by making the process more transparent, asking questions, and considering the social context of the data. They describe how tools from social science might be incorporated into data science practices, discuss different types of collaboration, and consider data storytelling through visualization. The book shows that data science practitioners can build rigorous \u003cu\u003eand\u003c\/u\u003e ethical algorithms and design projects that use cutting-edge computational tools \u003cu\u003eand\u003c\/u\u003e address social concerns.Acknowledgments ix\u003cbr\u003e1 Data Science to Human-Centered Data Science 1\u003cbr\u003e2 The Data Science Cycle 13\u003cbr\u003e3 Interrogating Data Science 31\u003cbr\u003e4 Techniques and Tools for Data Science Models 51\u003cbr\u003e5 Human-Centered Approaches to Data Science Problems 75\u003cbr\u003e6 Human-Centered Data Science Methods 93\u003cbr\u003e7 Collaborations across and beyond Data Science 115\u003cbr\u003e8 Storytelling with Data 129\u003cbr\u003e9 The Future of Human-Centered Data Science 147\u003cbr\u003eGlossary 153\u003cbr\u003eReferences 163\u003cbr\u003eIndex 179“We cannot engage in data science that doesn’t account for power. Histories and systems of race and gender must be taught to data scientists, because we know terrible wrongs can occur in the making and use of data. This book is a must-read to expose the next generation of data scientists to the consequences of their work.”\u003cbr\u003e—\u003cb\u003eSafiya Umoja Noble, author of \u003ci\u003eAlgorithms of Oppression\u003c\/i\u003e\u003c\/b\u003e\u003cbr\u003e \u003cbr\u003e“By centering both the human-centric perspective and the data scientific perspective equally, the authors craft a comprehensive approach to human-centered data science. This book is a useful handbook to developing forward-thinking data science teams who will be prepared for the next iteration of machine learning.”\u003cbr\u003e—\u003cb\u003eRumman Chowdhury, Director of ML Ethics, Transparency, and Accountability (META), Twitter\u003c\/b\u003e\u003cbr\u003e \u003cbr\u003e“This book’s unique approach recognizes that data science is a craft spun with subjective design choices. It will be invaluable to students and practitioners alike.”\u003cbr\u003e —\u003cb\u003eChris Wiggins, Chief Data Scientist, \u003ci\u003eNew York Times\u003c\/i\u003e\u003c\/b\u003eCecilia Aragon is Professor in the Department of Human Centered Design and Engineering at the University of Washington. Shion Guha is Assistant Professor in the Faculty of Information at the University of Toronto. Marina Kogan is Assistant Professor in the School of Computing at the University of Utah. Michael Muller is a Research staff member at IBM Research. Gina Neff is Director of the Minderoo Centre for Technology and Democracy at the University of Cambridge and Professor of Technology and Society at the Oxford Internet Institute and the Department of Sociology at the University of Oxford. \u003cbr\u003e \u003cbr\u003e ","brand":"The MIT Press","offers":[{"title":"Default Title","offer_id":46302302765285,"sku":"NP9780262543217","price":35.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780262543217.jpg?v=1767729520","url":"https:\/\/k12savings.com\/es\/products\/humancentered-data-science-isbn-9780262543217","provider":"K12savings","version":"1.0","type":"link"}