AncestryAI Algorithm Traces Your Family Tree Back More Than 300 Years

Aalto University, 3/16/2017

An Aalto University graduate student is developing a new family-tree algorithm called AncestryAI that uses Finnish parish registers to generate a probable family tree. Register data comes from HisKi, an open genealogical database supported by volunteer data entry. AncestryAI users can leave feedback on the accuracy of their tree, which is used to further train the algorithm.

Machine-Learning Algorithm Can Show Whether State Secrets Are Properly Classified

MIT Technology Review, 11/14/2016

Researchers from Columbia University and a Brazilian think tank have developed a machine-learning algorithm to predict whether now-declassified U.S. State Department cables from the 1970’s were unclassified, limited official use, confidential, or secret, based on contents and metadata such as sender and recipient. The study provides insight into how the information was classified, but also carries potential national security implications by highlighting trends in erroneous information classification — and systematic gaps where secret cables should have been declassified.

Big Data Help CIA Predict Social Unrest 5 Days Before It Begins

Tech Times, 10/7/2016

The CIA and their new Directorate of Digital Innovation are working on “anticipatory intelligence” to predict future events. The Deputy Director says that they can sometimes forecast outbreaks of unrest up to five days ahead. These predictions are made by using classified information as well as open source data; commentators speculate that much of the data comes from massive social media surveillance.

How Big Data and Algorithms Are Slashing the Cost of Fixing Flint’s Water Crisis

The Conversation, 09/08/2016

Beyond tech companies such as Amazon and Google, big data has a significant effect on science, engineering, and even plumbing. As the government in Flint, Michigan has worked to correct the dangerous levels of lead contamination reported earlier this year, researchers at the University of Michigan have aggregated and analyzed data for homes in the area. Their analysis is providing new insights into how the government can best direct their efforts, to reduce costs and increase impact.