Amazon cover image
Image from Amazon.com
Syndetics cover image
Image from Syndetics

Data science in context : foundations, challenges, opportunities / Alfred Z. Spector [and three others].

By: Material type: TextTextLanguage: English Cambridge : Cambridge University Press, 2023Description: 1 online resource (xvi, 316 pages) : digital, PDF file(s)Content type:
  • text
Media type:
Carrier type:
  • online resource
ISBN:
  • 9781009272230 (ebook)
Subject(s): Additional physical formats: No titleDDC classification:
  • 006.3/12
LOC classification:
  • QA76.9.D343 S64 2023
Online resources: Summary: 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.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)

Title from publisher's bibliographic system (viewed on 29 Sep 2022).

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.

There are no comments on this title.

to post a comment.
Share
This system is made operational by the in-house staff of the CUP Library.