acm-header
Sign In

Communications of the ACM

ACM News

The Battle to Prevent Another January 6 Features a New Weapon: The Algorithm


View as: Print Mobile App Share:
Supporters of President Donald Trump climb the west wall of the U.S. Capitol on Jan. 6, 2021.

Machine learning is being employed to try to predict future events like the storming of the U.S. Capitol on January 6, 2021, with intriguing but fraught results.

Credit: Jose Luis Magana/AP

For many Americans who witnessed the attack on the Capitol last Jan. 6, the idea of mobs of people storming a bedrock of democracy was unthinkable.

For the data scientists who watched it unfold, the reaction was a little different: We've been thinking about this for a long time.

The sentiment comes from a small group working in a cutting-edge field known as unrest prediction. The group takes a promising if fraught approach that applies the complex methods of machine-learning to the mysterious roots of political violence. Centered since its inception a number of years ago on the developing world, its systems since last Jan. 6 are slowly being retooled with a new goal: predicting the next Jan. 6.

"We now have the data — and opportunity — to pursue a very different path than we did before," said Clayton Besaw, who helps run CoupCast, a machine-learning-driven program based at the University of Central Florida that predicts the likelihood of coups and electoral violence for dozens of countries each month.

 

From The Washington Post
View Full Article

 


 

No entries found

Sign In for Full Access
» Forgot Password? » Create an ACM Web Account