Harvard & Google Seismic Paper Hit With Rebuttals: Is Deep Learning Suited to Aftershock Prediction?

The aftershocks that follow an earthquake can be even more dangerous and damaging than the main temblor, for example by collapsing already structurally weakened buildings. With deep learning emerging as something of a panacea in the world of science, AI researchers and seismologists alike are leveraging the tech in pursuit of better aftershock forecast solutions. A major breakthrough seemed to occur in 2018 when a Harvard University and Google research team published the paper Deep learning of aftershock patterns following large earthquakes in Nature. The paper proposed a deep learning model that significantly improved aftershock location forecasts compared to previous methods. It went viral on social media and garnered global mainstream media coverage.