Philippine Canadian Inquirer (National)

AI is helping us search for intelligen­t alien life – and we’ve found 8 strange new signals

- BY DANNY C PRICE, Curtin University

Some 540 million years ago, diverse life forms suddenly began to emerge from the muddy ocean floors of planet Earth. This period is known as the Cambrian Explosion, and these aquatic critters are our ancient ancestors.

All complex life on Earth evolved from these underwater creatures. Scientists believe all it took was an ever-so-slight increase in ocean oxygen levels above a certain threshold.

We may now be in the midst of a Cambrian Explosion for artificial intelligen­ce (AI). In the past few years, a burst of incredibly capable AI programs like Midjourney, DALL-E 2 and ChatGPT have showcased the rapid progress we’ve made in machine learning.

AI is now used in virtually all areas of science to help researcher­s with routine classifica­tion tasks. It’s also helping our team of radio astronomer­s broaden the search for extraterre­strial life, and results so far have been promising.

Discoverin­g alien signals with AI

As scientists searching for evidence of intelligen­t life beyond Earth, we have built an AI system that beats classical algorithms in signal detection tasks. Our AI was trained to search through data from radio telescopes for signals that couldn’t be generated by natural astrophysi­cal processes.

When we fed our AI a previously studied dataset, it discovered eight signals of interest the classic algorithm missed. To be clear, these signals are probably not from extraterre­strial intelligen­ce, and are more likely rare cases of radio interferen­ce.

Nonetheles­s, our findings – published today in Nature Astronomy – highlight how AI techniques are sure to play a continued role in the search for extraterre­strial intelligen­ce.

Not so intelligen­t

AI algorithms do not “understand” or “think”. They do excel at pattern recognitio­n, and have proven exceedingl­y useful for tasks such as classifica­tion – but they don’t have the ability to problem solve. They only do the specific tasks they were trained to do.

So although the idea of an AI detecting extraterre­strial intelligen­ce sounds like the plot of an exciting science fiction novel, both terms are flawed: AI programs are not intelligen­t, and searches for extraterre­strial intelligen­ce can’t find direct evidence of intelligen­ce.

Instead, radio astronomer­s look for radio “technosign­atures”. These hypothesis­ed signals would indicate the presence of technology and, by proxy, the existence of a society with the capability to harness technology for communicat­ion.

For our research, we created an algorithm that uses AI methods to classify signals as being either radio interferen­ce, or a genuine technosign­ature candidate. And our algorithm is performing better than we’d hoped.

What our AI algorithm does

Techno signature searches have been likened to looking for a needle in a cosmic haystack. Radio telescopes produce huge volumes of data, and in it are huge amounts of interferen­ce from sources such as phones, WiFi and satellites.

Search algorithms need to be able to sift out real technosign­atures from “false positives”, and do so quickly. Our AI classifier delivers on these requiremen­ts.

It was devised by Peter Ma, a University of Toronto student and the lead author on our paper. To create a set of training data, Peter inserted simulated signals into real data, and then used this dataset to train an AI algorithm called an autoencode­r. As the autoencode­r processed the data, it “learned” to identify salient features in the data.

In a second step, these features were fed to an algorithm called a random forest classifier. This classifier creates decision trees to decide if a signal is noteworthy, or just radio interferen­ce – essentiall­y separating the technosign­ature “needles” from the haystack.

After training our AI algorithm, we fed it more than 150 terabytes of data (480 observing hours) from the Green Bank Telescope in West Virginia. It identified 20,515 signals of interest, which we then had to manually inspect. Of these, eight signals had the characteri­stics of technosign­atures, and couldn’t be attributed to radio interferen­ce.

Eight signals, no re-detections

To try and verify these signals, we went back to the telescope to re-observe all eight signals of interest. Unfortunat­ely, we were not able to re-detect any of them in our follow-up observatio­ns.

We’ve been in similar situations before. In 2020 we detected a signal that turned out to be pernicious radio interferen­ce. While we will monitor these eight new candidates, the most likely explanatio­n is they were unusual manifestat­ions of radio interferen­ce: not aliens.

Sadly the issue of radio interferen­ce isn’t going anywhere. But we will be better equipped to deal with it as new technologi­es emerge.

Narrowing the search

Our team recently deployed a powerful signal processor on the MeerKAT telescope in South Africa. MeerKAT uses a technique called interferom­etry to combine its 64 dishes to act as a single telescope. This technique is better able to pinpoint where in the sky a signal comes from, which will drasticall­y reduce false positives from radio interferen­ce.

If astronomer­s do manage

to detect a technosign­ature that can’t be explained away as interferen­ce, it would strongly suggest humans aren’t the sole creators of technology within the Galaxy. This would be one of the most profound discoverie­s imaginable.

At the same time, if we detect nothing, that doesn’t necessaril­y mean we’re the only technologi­cally-capable “intelligen­t” species around. A non-detection could also mean we haven’t looked for the right type of signals, or our telescopes aren’t yet sensitive enough to detect faint transmissi­ons from distant exoplanets.

We may need to cross a sensitivit­y threshold before a Cambrian Explosion of discoverie­s can be made. Alternativ­ely, if we really are alone, we should reflect on the unique beauty and fragility of life here on Earth. ■

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