To settle the enduring debate surrounding the cause of the mass extinction event that occurred 66 million years ago, wiping out dinosaurs and various other species, researchers at Dartmouth College adopted a novel approach. Rather than relying on human interpretation, they opted to remove scientists from the equation and let computers make the determination.
The researchers report in the journal Science a new modeling method powered by interconnected processors that can work through reams of geological and climate data without human input. They tasked nearly 130 processors with analyzing the fossil record in reverse to pinpoint the events and conditions that led to the Cretaceous–Paleogene (K–Pg) extinction event that cleared the way for the ascendance of mammals, including the primates that would lead to early humans. To settle the enduring
Alex Cox, the first author of the study and a graduate student in Dartmouth’s Department of Earth Sciences, explained the motivation behind their approach, stating, “Part of our motivation was to evaluate this question without a predetermined hypothesis or bias.” In a departure from conventional models that progress forward, the researchers adapted a carbon-cycle model to operate in reverse. By employing statistics and providing the model with minimal prior information, they aimed to let the model discern the cause from the effect, working towards a specific outcome in a unique and unbiased manner.
The model crunched more than 300,000 possible scenarios of carbon dioxide emissions, sulfur dioxide output, and biological productivity in the 1 million years before and after the K–Pg extinction. Through a type of machine learning known as Markov Chain Monte Carlo — which is not unlike how a smartphone predicts what you’ll type next — the processors worked together independently to compare, revise, and recalculate their conclusions until they reached a scenario that matches the outcome preserved in the fossil record.