“Machine learning provides a way of providing almost human-like intuition to huge data sets. One valuable application is for tasks where it’s difficult to write a specific algorithm to search for something—human faces, for instance, or perhaps “something strange,” wrote astrophysicist and Director of the Penn State University Extraterrestrial Intelligence Center, Jason Wright in an email to The Daily Galaxy. “In this case, you can train a machine-learning algorithm to recognize certain things you expect to see in a data set,” Wright explains, “and ask it for things that don’t fit those expectations, or perhaps that match your expectations of a technosignature.
“For instance,’” Wright notes, “theoretical physicist Paul Davies has suggested crowdsourcing the task of looking for alien structures or artifacts on the Moon by posting imaging data on a site like Zooniverse and looking for anomalies. Some researchers (led by Daniel Angerhausen) have instead trained machine-learning algorithms to recognize common terrain features, and report back things it doesn’t recognize, essentially automating that task. Sure enough, the algorithm can identify real signs of technology on the Moon—like the Apollo landing sites!”
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