FECYT – Spanish Foundation for Science and Technology
An artificial neural network has identified a square structure within a triangular one in a crater on the dwarf planet Ceres, with several people agreeing on this perception. The result of this intriguing visual experiment, carried out by a Spanish neuropsychologist, calls into question the application of artificial intelligence to the search for extra-terrestrial intelligence (SETI).
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.
Now researchers from the University of Cadiz (Spain) have looked at one of these spots, called Vinalia Faculae, 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 analyse 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.”
“On the other hand,” he adds, “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?”
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.”
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References:
Gabriel G. De la Torre. “Does artificial intelligence dream of non-terrestrial techno-signatures?” Acta Astronautica 167: 280-285, February 2020.
Nailed it again.
Interesting article that points to the problems inherent in utilizing AI and the complexity of human vision. If the artificial vision AI were trained by examples of squares and triangles it was prompted to find them, no matter how subtle the signature. Why not train the AI to see all known shapes (sure, takes more time/money) and let it find what it might? Human vision is in the brain, utilizing digital clues via the optic nerve which gains its signals from rods and cones in the eye. However, the human brain fills in the view that is seen with its interpretation of what is going on. The vision processing even makes things move when they don’t move. It appears that women especially have peripheral vision that is set to signal alarms (something or someone is sneaking up on the children?). Since peripheral vision is mostly very inexact, and not stored in memory, the visual processing center in the brain calls attention to something unusual and even can make it appear to move when it is not moving. This is the brain demanding that the center of the eye be focused on the object in question. In golf it is common that standing diagonally behind a female golfer often produces a moving image and a request to move (not being sexist here, the same effect is found in a higher percentage of women than men). So, what to make of the report of AI and human vision? Be careful and only allow into stored memory something that can be verified by rigorous follow-on examination.
I fail to see why this weird experiment was conceived of and instigated in the first place. The conclusion could only ever be that any possible evidence of extra-terrestrial life, be it discovered by people or by machines, would always have to be debated and interpreted by us living human beings! Harebrained, useless research, in my opinion.
I am with many critics and what the paper shows is that dropkick researchers who know nothing of AI can get results that are as stupid as a human would produce.
I saw both the square and the triangle before I read the caption, but I have a lot of experience with aerial imagery. We know humans are excellent at perceiving patterns, particularly familiar ones such as geometric shapes or human faces, in all kinds of places, from aerial images to cracks in the ceiling. For humans, the challenge is be aware of this and not to jump to conclusions that seeing a familiar shape means aliens built that face on Mars. This experiment is useful is showing that AI can be trained to ‘see’ geometric shapes too. But can AI learn how to assess whether such shapes are artefacts of perception or artefacts built by aliens? If so, then AI would be more intelligent than many humans.
AI is pattern matching. There will be errors and illusions.As an aside, the fact that we cannot see anything faster than 1/16th. of second tells us how fast our pattern matching and detection machines work in the eye. Probably just a couple of training cycles.
I see a couple of triangles, a couple of rectangles, a bunch of lighters or cell phones, and Elvis.
Excerpted comment:
OH MY, …. GOLLY GEE, …. the programmer(s) of those above cited AI systems musta really outdone themselves, ……. by creating software that has “abstract reasoning” abilities far greater than their own.
Well “DUH”, …… now I wonder how that could possibly have ever happened?
Percival Lowell was right.
The canals of Mars and the Martians’ great cities and desperate works of geoengineering will some day be crisply revealed when we move past the grainy resolution of present-day Mars rovers. His glimpses and drawings were uncanny and accurate for features that are 1mm square.
I can’t see how this is a failure. They trained it to find squares and triangles, and it found them. They didn’t train it to find squares and triangles constructed by intelligent beings. Humans have been detecting “false and impossible” things for years (like canals on Mars – though not impossible). False positives and false negatives are simply inescapable results of detecting things.
I think the takeaway for SETI is to let the machines search through the data, but only have it confirmed by humans. But honestly, isn’t that their policy anyway?
There is a square-is something at the center of the photo (not really very square), but I just don’t see a triangle … someone needs to mark up the photo so that us less “gifted” people can see it too.
Just looking at the picture without being told what to look for, I would not have said I saw a square or a triangle. I would say I was looking at some rough terrain containing no sign of an artificial construct.
Why the assumption that it was wrong and that this cannot be ET?
There’s also the giant flat-topped “pyramid”, Ahuna Mons, on Ceres. Was it constructed by aliens? Ancient astronaut theorists say yes….. 😉
Square-ish and triangle-ish shapes. What in the heavens is unusual in detecting such patterns? Zooming in or out from the reference frame one would be hard pressed to not find many examples of geometrical-ish patterns. Can AI see the ‘Man in the Moon’?
Within the square I see a pie-chart with a piece missing around 9 o’clock.
Signals of unknown… assumed… asserted fidelity. Would an “AI” discovery of patterns in the chaos add to the data, or to the information?
No one was talking about triangles or squares, or aliens for that matter, here…
https://www.jpl.nasa.gov/spaceimages/details.php?id=PIA21925
or saw them here…
http://cdn.sci-news.com/images/enlarge5/image_6229_2e-Vinalia-Faculae.jpg
from
http://www.sci-news.com/space/ceres-bright-spots-spectacular-detail-06229.html
The artificial neural network would appear to need some refining…perhaps get it to identify shapes in clouds
To call either of these shapes a “square” or a “triangle” is a stretch anyway. On the image presented, the best that can be said is that it is a “square-ish” shape in a “triangle-ish” shape.
What would it make of this I wonder ? (Basalt columns)
https://images.app.goo.gl/bBWHsHk8WjKgarbX8
” … search for extraterrestrial life (SETI) …”
should be
Search for Extraterrestrial Intelligence (SETI)
No Jodie Foster for you!