Энэ электрон номын тухай
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.
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.
Зохиогчийн тухай
Sarah Williams is Associate Professor of Technology and Urban Planning at the MIT School of Architecture and Planning, where she is also Director of the Civic Data Design Lab. Trained in geography, landscape architecture, and urban planning, she was named one of the Top 25 Leading Thinkers in Urban Planning and Technology by Planetizen and 2012 Game Changer by Metropolis Magazine. Her designs and visualizations have been widely exhibited.
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