Knight News Challenge on Data winners

Today the Knight Foundation announced the winners of the Knight News Challenge on Data.

Thanks to everyone who threw their hat in the ring, and congrats to the winners.

“The winners highlight data as an essential element in addressing community challenges and opening opportunities for learning and innovation. They address issues from police misconduct and digital privacy, to expanding access to public benefits, to improving data literacy and making it easier to find and use public information.”

As collaborators on this Challenge, along with Open Society Foundations, we’re pleased to share today’s news — and we’re super pleased for the serious work of the funded projects to begin. This KnightBlog post introduces the eight winning projects, plus an additional nine that will receive support through the Knight Prototype Fund.

We’re looking forward to engaging with and learning from what they build and discover!

All the projects are thought-provoking. A couple caught our eye:

Law, Order & Algorithms: Making Sense of 100 Million Highway Patrol Stops will compile, analyze, and release one of the most comprehensive data sets of police interactions with the public.

Citizens Police Data Project will build an online toolkit for reporting, tracking, and analyzing allegations of police misconduct and their investigations in Chicago.

Both of these projects will add to understanding of the relation between data and accountability in law enforcement contexts, a tricky issue we continue to think through (cf. materials from the second Data & Civil Rights conference: A New Era of Policing and Justice).

All the Places Personal Data Can Go: Building upon the work of theDataMap, Latanya Sweeney and team will create a detailed database of personal data sharing arrangements among companies and organizations that can be visualized, and help the public spot potential risks, benefits and opportunities.

The amazing research of Latanya Sweeney, who also serves on the Council for Big Data, Ethics, and Society, has helped to orient a number of inquiries here at Data & Society, especially those touching on discrimination and automated data flows (see, for example, the citation in What World Are We Building? by danah boyd).

Could Your Data Discriminate? This project, from Data & Society fellows Sorelle Friedler and Wilneida Negrón, will help people learn about data discrimination through a website that will allow people to test data for bias and experiment with public data to determine what may result in such bias.

We’re excited to host a project that will take some of the themes of our Data & Fairness initiative and translate them into an interactive, public-facing resource.

Quantified Self Data Experience: Understanding Your Data and the World it Creates: Informing people about digital privacy, data sharing and the future of our data-driven society using performance, interactive art, more.


Now go read about all the winning projects.