Author: Sara Hooker
Publisher: Medium
Publication Year: 2018
Summary: The following article discusses how data for good has become an arbitrary goal and means little with regards to the tools being used, the goals of the project, or who the project serves. This can be a useful term when discussing with a general audience, but amongst data professionals, more precision is needed to describe the work being done and where we can work better. The article bins current “data-for-good” projects into 4 categories: 1). Volunteerism, 2). Donated/subsidized tools, 3). Non-profit or government agencies that receive the data product, and 4). Educational programs that aim to build technical skills in underserved communities. Each of these categories carries its own risks and potential, so knowing the aim of the project is important.