AI spots tiny earthquakes that humans can't feel
When I first stared at a seismogram, all I saw were endless squiggles that a seasoned analyst had to tease apart. It was slow work, and the tiniest tremors often vanished into the background. These days AI is taking over that grunt work.
New algorithms can automatically flag micro-earthquakes, quakes so small you wouldn’t feel them, things that used to be buried in the noise. It’s a bit like slipping on glasses for the first time; suddenly a whole layer of seismic chatter becomes visible.
That extra detail isn’t just for the sake of numbers. Those microquakes help map hidden fault lines and give clues about underground stress. In California, AI runs around the clock, picking up thousands of these tiny events and feeding them to scientists in near real-time. What once took weeks of manual slog can now be processed in hours, turning a tedious chore into a steady stream of useful insight.
Still, this earthquake is notable, not because it was large but because it was small—and yet we know about it. Over the past seven years, AI tools based on computer imaging have almost completely automated one of the fundamental tasks of seismology: detecting earthquakes. What used to be the task of human analysts—and later, simpler computer programs—can now be done automatically and quickly by machine learning tools.
These machine learning tools can detect smaller earthquakes than human analysts, especially in noisy environments like cities. Earthquakes give valuable information about the composition of the Earth and what hazards might occur in the future. “In the best-case scenario, when you adopt these new techniques, even on the same old data, it’s kind of like putting on glasses for the first time, and you can see the leaves on the trees,” said Kyle Bradley, co-author of the Earthquake Insights newsletter.
I talked with several earthquake scientists, and they all agreed that machine learning methods have replaced humans for the better in these specific tasks.
The real punch of this AI-driven seismic analysis isn’t simply that we can list more quakes. It feels more like a shift in how we listen to the planet’s constant, subtle shivers. For decades we built our picture of faults and risk from only the biggest shakes, the ones that made headlines.
Now the algorithms are pulling out thousands of barely-noticeable tremors that used to slip under the radar, so for the first time we’re seeing something close to the whole puzzle. Think of it as sharpening a blurry map: the extra detail lets researchers track how stress builds and hops along a fault line, which could tighten up long-term hazard models. It’s probably true that we still can’t point to the exact moment a mega-quake will strike, but the forecasts we make about regional risk are becoming a lot more grounded in data.
In other words, the low-level hum that was once lost in the noise is turning into a surprisingly useful clue.
Resources
- AI finds ten times more earthquakes than previous methods - Warp News
- How AI is helping to detect earthquakes - Context by Thomson Reuters Foundation
- AI model reveals hidden earthquake swarms and faults in Italy's Campi Flegrei - Stanford Sustainability
- How Science Is Using AI to Translate the Nonstop Chatter of the Earth - National Academies
- Shaking Things Up: How BU Researchers Are Driving Earthquake Understanding Through Artificial Intelligence - Boston University Hariri Institute
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Common Questions Answered
How do AI tools automate the detection of tiny earthquakes that were previously missed?
AI tools based on machine learning and computer imaging automatically scan seismogram data to identify faint tremors that are too small for humans to feel. This automation replaces the slow, tedious work previously done by human analysts and simpler computer programs, allowing for rapid detection of seismic events that were once lost in the noise.
What fundamental task of seismology has been almost completely automated by AI over the past seven years?
The fundamental task of detecting earthquakes has been almost completely automated by AI tools in recent years. These machine learning systems can now perform what was once the primary responsibility of human experts, enabling the identification of smaller earthquakes quickly and automatically.
How does AI-driven seismic analysis change our understanding of fault lines and seismic risk?
AI-driven seismic analysis reveals thousands of tiny tremors that were previously invisible, providing a much richer and more granular picture of the Earth's constant movements. This allows scientists to understand fault line behavior and assess seismic risk based on nearly the full spectrum of activity, rather than just the large earthquakes that humans can notice.