Human-Centered Data Science: An Introduction

Human-Centered Data Science Produced with University of Washington, Seattle

Human Centered Data Science was written by five authors in a five day Book Sprint and is now published by MIT Press.

The Book Sprint was hosted in 2020 at the University of Washington in Seattle with a small team of professors who pioneered this new field of human-centered data science. The idea was to write the handbook for new data science practitioners and students to help shed light on the potential bias and inequality resulting from automated collection, analysis, and distribution of large datasets.

As described on the MIT website:

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.

Cecilia Aragon who organised the Book Sprint said:

I am so grateful we got our Book Sprint in under the wire.  All is going well and we are very happy with the Book Sprint for helping us accomplish our goal of collaboratively writing a first draft of our book.

The Authors

Cecilia Aragon

Shion Guha

Marina Kogan

Michael Muller

Gina Neff


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