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.
Ron L. ….. peripheral vision has nothing whatsoever to do with a female’s or mother’s intuition.
“ a thing that one knows or considers likely from instinctive feeling rather than conscious reasoning. ”
“Instinctive feeling” can either be an inherited “survival instinct” …… or a “nurtured trait” as a result of environmental stimuli.
“Instinctive feeling” in all animals is another word for “pattern recognition.” Why is it that no one was describing unknown sky phenomena as “spaceships” before the sci-fi era? Not “alien abductions,” the same hallucinations were couched in religious language–“incubi and succubi” or being impregnated by angels or demons.
Before any “search for extraterrestrials” soaks up any more taxpayer money, the question should be asked: What the hell would we do if we FOUND some? What is the goal here? Defense, trade, communication, assimilation of superior technology? “Yeah, that’d be cool!” is not a strategy in pursuit of a question with world-altering implications for the entire human race.
Personally, I think this belongs on “Coast-to-Coast AM” (a wee-hours paranormal entertainment radio program) and Global Warming agitprop right there with it–alongside Bigfoot, ghosts, the Loch Ness Monster, and crystal-ball ladies who talk to the dead!
People who don’t believe in alien visitations are just skeptics who haven’t been anal-probed yet.
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.
AIs will be expected in future to be able to scan data/images at very much faster rates than humans can is the short answer. No doubt there were plenty of people back in the 14th century who thought there was no point in sailing beyond the western horizon of wherever . . . maybe they were right. May not. But here we are, and so long as there are humans on this planet some of them will be driven to look beyond what and where we know. And one day, that just might prove to be a good thing . . . Maybe as we learn to see further beyond ourselves we’ll also learn to see more of what’s within us.
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.
It’s called artificial intelligence, but the practice of programming an intelligent machine also means we create artificial stupidity. If you go back to Newell’s rather complete descriptions of human problem solving, and the tasks that are required, there is a clear possibility that machine problem solving will lead to the same massive blunders made by many humans
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.
I remember the “canali” on Mars, human eyes use to complete whar ever shapes to known structures.
Wow, you are old !! This was contemporaneous with Arrhenius (1896), with neither conjecture turning into a valid hypothesis.
You don’t have to be as old as Arrhenius, or Lowell, to remember the Martian canals. Here’s a map of Mars the US Air Force produced in 1962. http://www.planetary.org/multimedia/space-images/mars/united-states-air-force-map-mars.html.
I once went to a lecture, probably 1980s, that analysed the way NASA had judiciously used pictures of the speculated Martian canals in its early PR publications lobbying for more space research. As I remember, the researcher showed how pictures of the alleged canals were juxtaposed with the hard news of how much money was needed, using the romantic hook of potential exciting discoveries; while pictures of technology, rocket engines and scientists were juxtaposed with text about the risks involved. I may not have that quite right, but the suggestion was that some clever editing had been done to sell the case. I can’t remember exactly when this was or the speaker, but it would have been Sydney or Canberra. Does this ring a bell with anyone else?
Finally, here’s an interesting theory about what actually Lovell saw.
http://jimokane.blogspot.com/2012/11/percival-lowell-and-blood-vessels-of.html
Cool stuff Tom, thanks.
Tom there is a deeper problem, these fools associate triangle and square shapes to alien presence. Anyone remotely across AI knows one does not simply pick parameters in this way and the fact they did it shows they know nothing of the field of AI.
Teaching an AI like that would mean it would miss alien life just because that race thought that squares and triangle had bad karma. You can imagine an alien life form that built using only fractals, the AI could look at a whole city built using fractals and it would conclude there was no life.
What they are doing doesn’t remotely go towards there stated goal because they are out of there depth.
A lot of what both the AI and people see in the image are errors of the poor resolution, lack of sharpness, and uneven contrast. Both artificial “intelligence” and human vision depend heavily on line detection, angular relationships, intensity gradients and other signals. A lot of human vision processing takes place in the retina itself and the layers that support it, the optic chiasm, and the structures in the brain where the optic signals end up.
The end result is the brain can “see” almost anything it wants to or is trained to. The result that you see depends also depends on the environment you are seeing in. In an unfamiliar environment, such as an airplane falling in a spin or a snap roll can easily confuse the brain about what it sees. So in the image almost all the “shapes” are errors because the brain has no way to categorize them but that they match things it is familiar with. It may see a triangle or square but that doesn’t mean is actually shows something that is triangular or square. It may be a triangle or it may simply be an error.
Tom Foley – January 29, 2020 at 3:18 am
Actually, all animals with good “eyesight” are excellent at perceiving patterns ….. but only if “parts n’ pieces” of said pattern (geometric shapes, human faces, cars, etc., etc.) had been previously “uploaded” via the eyes/optic nerves and stored as “bits n’ pieces” in the brain’s neurons.
That’s why one cannot recognize a complete stranger, but has no trouble recognizing their spouse, children, friends, etc., even if they can only see the back of their head, the clothes they are wearing ….. or hear their voice on the telephone.
The subconscious mind can “upload” a very small segment of environmental data …… and compose a complete “picture” around it ….. if it “matches” data that is stored in a neuron.
Anyone that has ever played the game “Clue” ……. knows exactly how their brain/mind works ….. but don’t know enough to explain it.
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.
Upon closer examination I also see a red Tesla convertible with a spaceman connecting a solar panel to its tailpipe.
Wow, you’re good at this. Time to move to the next level. I can only see the face of the giant that built this structure on this celestial body:
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?
AI systems suffer from the same problems as their creators
Ditto for climate models.
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.
The movie “Invaders from Mars” scared me when I was a kid. The heroes were able to get dynamite into the buried saucer which blew up as it was coming out of the ground:
https://youtu.be/EJMgz6ZG-2w
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.
The triangle just encloses the square and points up with the vertex at about 1 o’clock.
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!