Human-Centered Data Science: An Introduction

Synopsis

Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets.Human-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. The 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 and ethical algorithms and design projects that use cutting-edge computational tools and address social concerns.

Copyright:

2022

Book Details

Book Quality:

Publisher Quality

ISBN-13:

9780262367592

Related ISBNs:

9780262543217

Publisher:

MIT Press

Date of Addition:

03/01/22

Copyrighted By:

Cecilia Aragon, Shion Guha, Marina Kogan, Michael Muller, and Gina Neff

Adult content:

No

Language:

English

Has Image Descriptions:

No

Categories:

Nonfiction, Science, Computers and Internet, Law, Legal Issues and Ethics

Submitted By:

Bookshare Staff

Usage Restrictions:

This is a copyrighted book.