Artificial intelligence (AI) systems are learning to do many tasks that are complex for people. Rare is the week in which we do not know its application or advances in some new area. Well, this Monday, an American team reveals that an AI system is doing quite well – with 90% reliability – to perform a key step in the search for life outside Earth: distinguish whether the origin of samples is biological or not (abiotic). Or what is the same, if those samples indicate that there are (or were) living organisms in that place.

Looking for traces of extraterrestrial life, past or present, is the great desire of scientists. This research is carried out within our solar system with robotic missions such as those of the Curiosity or Perseverance vehicles on Mars, and on much more distant worlds (exoplanets or extrasolar planets) through other techniques and telescopes that try to detect those worlds outside the Solar System biosignatures or biomarkers, that is, elements that may indicate signs of life. as we know it on Earth.

These biosignatures (elements, isotopes, molecules or phenomena that provide evidence that there has been or was life) include molecular oxygen, ozone or methane. But the fact that one of these elements exists does not necessarily mean that there is life, that is, that it is a biomarker. For example, on Earth methane is produced by living beings such as bacteria or cows. This gas has also been detected on Mars, but the origin could be both volcanism and biological processes.

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In the same way, there are organic components that have been produced by biological activity (by living beings) or non-biological, and it is there, in the distinction between the two, where the artificial intelligence system is being trained that this Monday presents in the journal Proceedings of the National Academy of Sciences (PNAS) a team led by Jim Cleaves and Robert Hazen, of the Carnegie Institution for Science, in the USA.

As astrobiologist and mineralogy specialist Robert Hazen explains, they started from "the idea that the chemistry of life differs fundamentally from that of the inanimate world, that there are 'chemical rules of life' that influence the diversity and distribution of biomolecules. If we could deduce those rules, we could use them to guide our efforts to model the origins of life or to detect subtle signs of life on other worlds."

Their AI system was trained on molecular analysis data from 134 carbon-rich samples, both biological and non-biological. According to this study, the AI was able to distinguish biotic samples from abiotic samples by detecting subtle differences in the molecular patterns obtained after analysis with instruments that separate and identify the components of a sample, and that determine the molecular weights of those components respectively. Specifically, the AI correctly identified the origin of samples of living organisms (such as modern shells, bones, teeth, insects, leaves or hair), remains of ancient life altered by geological processes (coal, carbon-rich fossils, oil or amber) and samples of non-biological origin.

According to Hazen, their method of analysis "has the potential to revolutionize the search for extraterrestrial life and deepen our knowledge of the chemistry and origin of the first forms of life on Earth," as they also want to use it to analyze ancient terrestrial rocks about which there is scientific debate. For example, 3.500 billion-year-old sediments found in Western Australia that some researchers say contain the oldest microbe fossils, while others argue that they contain no traces of ancient life.

Rocks found in Australia 3,500 million oldCARNEGIE INST.

The American astrobiologist believes that this AI system could be incorporated into smart sensors that would carry spacecraft and robotic vehicles to search for signs of life before bringing the samples back to Earth.

Jorge Pla-García, researcher at the Center for Astrobiology (CAB / CSIC-INTA), without connection to the study published in PNAS, considers that it is "a very interesting research that could help astrobiologists in the future when determining if, indeed, any of the samples analyzed outside the Earth are really biomarkers". This scientist, who is a member of the Spanish team that has supplied NASA with the weather stations that carry its Martian rovers and has signed numerous studies on the presence of methane on Mars, recalls "that only that organic compound that comes clearly and univocally from biological activity is a biomarker. And this is not so easy to discern. On our own planet it is difficult to find and confirm signs of past life in rocks of the Early Earth (as the early phases of our planet are known). If doing this here at home is really complex, imagine doing it remotely on Mars, a planet far from us at an average distance of 225 million km."

To prove that a sample is of biological origin, adds Pla-García, "not only must you be able to demonstrate that life can create it, but you have to rule out that it was created by other processes. It is precisely at this point where AI plays a fundamental role according to this team of researchers and so the results seem very promising, although we also have to be cautious, since they speak of an accuracy of 90%, a fairly high value but not enough to discern univocally whether or not a compound comes from biological activity (in astrophysics for example, to confirm that a compound is present in the atmosphere of an exoplanet, we need an accuracy of 99.977%)," he says.


One of the great problems that the astrobiological community faces daily is the in situ analysis of the samples, due to the limited performance of the instrumentation on board space missions compared to the very powerful and ambitious laboratories we have on Earth. It is for this reason that to try to identify the origin of the Martian samples identified as of high astrobiological interest according to the Perseverance rover, we need to bring them back to Earth with the future Mars Sample Return (MSR) mission."

However, as the Spanish scientist recalls, an independent review published last week concludes that this mission could cost more than 10,000 million euros and suggests that NASA delay or replan it: "Perhaps, in the future, AI will help us study samples remotely without having to bring them home. This new research opens a new range of possibilities," says Pla-García, who considers that AI is "a very powerful tool" that they already use in their own research group to improve weather predictions on Mars, he says.