AI and Earthquake Detection: A Closer Look

When it comes to artificial intelligence (AI), there is often a mix of fear and fascination surrounding its capabilities. Many people are unsure of what AI truly entails and how it can be applied to real-world scenarios. One area where AI is making significant strides is in earthquake detection, early warning systems, prediction, and tsunami forecasting.

The Evolution of AI in Seismology

Computers and algorithms have been integral to seismology for over fifty years. In the past, researchers would manually input data using punch cards, a tedious and error-prone process. However, with the advent of AI, programs can now learn and adapt without human intervention.

Machine learning (ML) is a crucial component of AI, allowing systems to analyze vast amounts of data and identify patterns. A familiar example of ML in action is spam phone call recognition, where the system learns to identify and block unwanted calls based on user feedback.

Everyday Applications of AI

AI is already a part of our daily lives, from fraud detection in banking to personalized ads on social media. The accuracy and usefulness of AI depend on the quality and quantity of data it processes.

The Role of AI in Earthquake Prediction

One of the most challenging tasks in seismology is predicting earthquakes with a lead time of days to weeks. While current systems like the USGS ShakeAlert can provide immediate warnings, long-term forecasting remains elusive.

Researchers are exploring various AI-driven approaches to earthquake prediction, with China leading the way in this field. A recent international contest hosted by China saw impressive results, with the University of Texas team accurately predicting 70% of earthquakes during a trial period.

AI and Tsunami Forecasting

AI is also revolutionizing tsunami forecasting, with researchers like Chris Moore from NOAA using deep ocean instruments to improve wave height estimates. By training AI models with simulated earthquake data, scientists can make accurate forecasts based on real-time information.

While AI shows promise in enhancing earthquake and tsunami warning systems, it is essential to remember that natural disasters can still pose significant risks. Ground shaking remains a crucial indicator for tsunami hazards, reminding us to stay vigilant in the face of potential dangers.

For a more detailed overview of AI and machine learning, visit https://mitsloan.mit.edu/ideas-made-to-matter/machine-learning-explained.

Lori Dengler is an emeritus professor of geology at Cal Poly Humboldt, specializing in tsunami and earthquake hazards. For questions or comments, contact Lori at 707-826-6019 or email Kamome@humboldt.edu.