AUSTIN, TX – (INT) - At the center of earthquake preparedness is, arguably, the field’s most controversial area of research: predicting when a quake will strike. Many scientists have long considered earthquake forecasting to be impossible—or, at best, they have approached it with extremely tempered optimism.

Even as recently as 2013, “the very topic of earthquake prediction was deemed unserious, as outside the realm of mainstream research as the hunt for the Loch Ness Monster,” writes seismologist Allie Hutchison for MIT Technology Review. And the U.S. Geological Survey maintains that “neither the USGS nor any other scientists have ever predicted a major earthquake.”

But given recent improvements in artificial intelligence, some researchers have been studying whether that could change. “I can’t say we will, but I’m much more hopeful we’re going to make a lot of progress within decades,” Paul Johnson, a seismologist working with machine learning at Los Alamos National Laboratory, told Smithsonian magazine’s Matthew Berger in 2019. “I’m more hopeful now than I’ve ever been.”

Last fall, researchers at the University of Texas at Austin bolstered such hopes for earthquake prediction with a seven-month trial in China. In their study, published in the Bulletin of the Seismological Society of America in September, an A.I. algorithm correctly predicted 70 percent of earthquakes one week before they happened. The team trained the A.I. on five years of seismic recordings, then asked it to locate upcoming quakes based on current seismic activity.

In all, the algorithm successfully forecasted 14 earthquakes, each within about 200 miles of its actual epicenter. Meanwhile, it missed one quake and predicted eight that never happened.

The trial was part of an international A.I.-design competition, one of a few such events held in recent years to advance earthquake prediction technologies.

“Predicting earthquakes is the holy grail,” Sergey Fomel, a geoscientist at UT Austin and a member of the research team, says in a statement. “We’re not yet close to making predictions for anywhere in the world, but what we achieved tells us that what we thought was an impossible problem is solvable in principle.”

Story Date: April 30, 2024