Scientists at the University of California, Los Angeles (UCLA) are developing an artificial intelligence tool to accelerate the search for evidence of extraterrestrial civilizations, using the help of society at large.
The team, led by Jean-Luc Margot, professor of earth, planetary and space sciences, analyzes radio signals to distinguish between signals from local sources, such as telecommunications systems or radars, and signals from extraterrestrial origin.
Among those that originate from deep space, he seeks to distinguish between those caused by natural phenomena, such as quasars and supernovae, and those that could be created by technical means.
The latter are called “technological signatures” by astronomers.
“Basically, we are looking for other engineers in the outer galaxy,” Margo told Efe.
The project is based on radio waves because, according to this scientist, “they are very easy to generate, they travel at the speed of light, and the universe is very transparent to them, which makes them very convenient to communicate” on a cosmic scale. .
Since 2016, the UCLA team has been using the Green Bank Telescope in West Virginia, the world’s largest fully steerable radio telescope, to detect radiation from stars and planetary systems.
“We have studied about 41,000 stars and recorded about 64 million signals,” the scientist emphasized.
Of the signals received, approximately 99.8% are classified by the project’s computer system as man-made radio interference, leaving hundreds of thousands of the most promising signals still under human review.
But a new tool the team is developing aims to make that search easier.
On February 14, the program invited everyone to help in signal classification, which requires only a computer or a “smartphone”.
Volunteers receive a brief briefing and must study radio wave images and answer simple questions, such as whether they are oriented vertically or horizontally.
They then have to select from a set of illustrations of common types of radio interference the one that best fits the signal they have analyzed.
At the same time, scientists are striving to create artificial intelligence algorithms – sets of precise instructions – that distinguish signals more efficiently.
“The artificial intelligence tool that we are building with the help of citizen scientists will automatically recognize and eliminate the most persistent types of interference and speed up our search, as we can focus on the most interesting signals,” said Margot Efe.
For the teacher, the partnership can cement the conversation about life beyond Earth in science rather than fantasy.
Margo also stressed that she is “delighted with the incredible response from the public”, specifying that after the 236 experts of the previous stage completed 5,000 classifications, “thousands of volunteers have provided 200,000 classifications” since the start of the citizen cooperation initiative, and there are still people who waiting to join this mission.
The scientist assured that he was not discouraged by the fact that so far no evidence of the existence of life outside the planet Earth has been found.
“Absence of evidence is not evidence of absence. We haven’t searched for a long time, so it’s not surprising that we still haven’t found anything. The search volume is huge, but our features and algorithms continue to improve every day, and I am excited about this investigation,” he concluded.