- Sold out
/https://libri-media.knygos-static.lt/55a04a49-64b4-4523-ac55-b49425f19fbd/2)
- Author: Sarah Williams
- Publisher: The MIT Press
- Year: 2020
- Pages: 285
- ISBN-10: 0262044196
- ISBN-13: 9780262044196
- Format: 23.6 x 26.1 x 2.7 cm, kieti viršeliai
- Language: English
Reviews
Description
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.
- Author: Sarah Williams
- Publisher: The MIT Press
- Year: 2020
- Pages: 285
- ISBN-10: 0262044196
- ISBN-13: 9780262044196
- Format: 23.6 x 26.1 x 2.7 cm, kieti viršeliai
- Language: English English
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.
Reviews