“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.
Crowdsourcing Alien Structures
“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!”
Phenomena Beyond the Human Level of Consciousness?
“If AI identifies something our mind cannot understand or accept, could it in the future go beyond our level of consciousness and open doors to reality for which we are not prepared? What if the square and triangle of Vinalia Faculae in Ceres were artificial structures?” asked Spanish clinical neuropsychologist Gabriel G. De la Torre about the application of artificial intelligence to the search for extra-terrestrial intelligence, and the identification of a possible technosignature –a square structure within a triangular one in a crater on the dwarf planet Ceres.
The result of this intriguing visual experiment calls into question the application of artificial intelligence to the search for extraterrestrial intelligence (SETI).
De la Torres research study, Does artificial intelligence dream of non-terrestrial techno-signatures? suggests that one of the “potential applications of artificial intelligence is not only to assist in big data analysis but to help to discern possible artificiality or oddities in patterns of either radio signals, megastructures or techno-signatures in general.”
“Our form of life and intelligence,” observed Silvano P. Colombano at NASA’s Ames Research Center not involved in the Ceres experiment, “may just be a tiny first step in a continuing evolution that may well produce forms of intelligence that are far superior to ours and no longer based on carbon “machinery.”
The result of De la Torre’s intriguing visual experiment calls into question the application of artificial intelligence to the search for extra-terrestrial intelligence (SETI) where advanced and ancient technological civilizations may exist but be beyond our comprehension or ability to detect.
Ceres’ Occator Crater
Ceres, although the largest object in the main asteroid belt, is a dwarf planet. It became famous a few years ago for one of its craters: Occator, where some bright spots were observed, leading to all manner of speculations. The mystery was solved when NASA’s Dawn probe came close enough to discover that these bright spots originated from volcanic ice and salt emissions.
Researchers from the University of Cadiz (Spain) have looked at one of these spots, called Vinalia Faculae (image above), and have been struck by an area where geometric shapes are ostensibly observable. This peculiarity has served them to propose a curious experiment: to compare how human beings and machines recognize planetary images. The ultimate goal was to analyze whether artificial intelligence (AI) can help discover ‘technosignatures’ of possible extra-terrestrial civilizations.
“We weren’t alone in this, some people seemed to discern a square shape in Vinalia Faculae, so we saw it as an opportunity to confront human intelligence with artificial intelligence in a cognitive task of visual perception, not just a routine task, but a challenging one with implications bearing on the search for extraterrestrial life (SETI), no longer based solely on radio waves,” explains Gabriel G. De la Torre.
The team of this neuropsychologist from the University of Cadiz, who has already studied the problem of undetected non terrestrial intelligent signals (the cosmic gorilla effect), now brought together 163 volunteers with no training in astronomy to determine what they saw in the images of Occator.
They then did the same with an artificial vision system based on convolutional neural networks (CNN), previously trained with thousands of images of squares and triangles so as to be able to identify them.
“Both people and artificial intelligence detected a square structure in the images, but the AI also identified a triangle,” notes De la Torre, “and when the triangular option was shown to humans, the percentage of persons claiming to see it also increased significantly.” The square seemed to be inscribed in the triangle.
These results, published in the Acta Astronautica journal, have allowed researchers to draw several conclusions: “On the one hand, despite being fashionable and having a multitude of applications, artificial intelligence could confuse us and tell us that it has detected impossible or false things,” says De la Torre, “and this therefore compromises its usefulness in tasks such as the search for extra-terrestrial technosignatures in some cases. We must be careful with its implementation and use in SETI.”
Finally, the neuropsychologist points out that AI systems suffer from the same problems as their creators: “The implications of biases in their development should be further studied while they are being supervised by humans.”
De la Torre concludes by acknowledging that, in reality, “we don’t know what it is, but what artificial intelligence has detected in Vinalia Faculae is most probably just a play of light and shadow.”
The Last Word –”AI Astronauts”
“Once our artificial intelligence (AI) systems will be able to autonomously explore scientific data and make discoveries on their own without human intervention, advances in our scientific knowledge will accelerate dramatically,” Harvard astrophysicist Avi Loeb wrote in an email to The Daily Galaxy. “Scientific progress will be freed from the chains of human ego that currently slow it down. Discoveries will not be choked anymore by prejudice and jealousy which curb innovation in academia.
“If other civilizations reached the “AI science” turning point,'” Loeb observes, “their AI scientists could serve as long-lived technological-astronauts who explore interstellar space with far more knowledge and intelligence than human-astronauts possess.
“The Galileo Project searches for possible AI astronauts from other planets,” Loeb explains, referring to the new search for extraterrestrial technological signatures complementary to traditional SETI, in that it searches for physical objects, and not electromagnetic signals, associated with extraterrestrial technological equipment. “This makes sense since our civilization is sending equipment to space; a major fraction of all sun-like stars host an Earth-size planet in their habitable zone; and many sun-like stars formed billions of years before the sun. It is therefore not an unreasonable proposition to imagine that out of the tens of billions of Earth-like planets within our Milky Way galaxy, at least one hosted a technological civilization that filled the Milky Way with AI-astronauts. To find out whether we live in such a reality, we must search the sky through our telescopes and use our own AI systems to find their siblings from outer space.
“Here’s hoping for future generations of AI scientists, both on Earth and in space,” Loeb concludes.
Source: Gabriel G. De la Torre. “Does artificial intelligence dream of non-terrestrial techno-signatures?” Acta Astronautica 167: 280-285, February 2020.
Image credit top of page: Alien technology, Shutterstock License