logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Data Action Sarah Williams

  • SKU: BELL-21979790
Data Action Sarah Williams
$ 35.00 $ 45.00 (-22%)

4.4

102 reviews

Data Action Sarah Williams instant download after payment.

Publisher: MIT Press
File Extension: EPUB
File size: 36.14 MB
Pages: 310
Author: Sarah Williams
ISBN: 9780262044196, 9780262359153, 9780262545310, 0262044196, 0262359154, 0262545314
Language: English
Year: 2020

Product desciption

Data Action Sarah Williams by Sarah Williams 9780262044196, 9780262359153, 9780262545310, 0262044196, 0262359154, 0262545314 instant download after payment.

How to use data as a tool for empowerment rather than oppression. Big data can be used for good--from tracking disease to exposing human rights violations--and for bad--implementing surveillance and control. Data inevitably represents the ideologies of those who control its use; data analytics and algorithms too often exclude women, the poor, and ethnic groups. In Data Action, Sarah Williams provides a guide for working with data in more ethical and responsible ways. Too often data has been used--and manipulated--to make policy decisions without much stakeholder input. Williams outlines a method that emphasizes collaboration among data scientists, policy experts, data designers, and the public. This approach creates trust and co-ownership in the data by opening the process to those who know the issues best.

Related Products