How big data forced the hunt for extraterrestrial intelligence to evolve

The hunt for intelligent life beyond Earth began as a niche field, with just a handful of researchers who scrambled to get the access to telescopes that they needed for their search for extraterrestrial intelligence (SETI). But in the last decade, spurred by the discovery of over 4,000 planets outside of our solar system, interest in the topic has exploded.

With more universities and research institutions getting involved in SETI, there are more telescopes than ever looking for direct or indirect technosignatures, which are indicators of technology such as the presence of radio waves. And Moore’s Law of increasing computer power means more and more data can be gathered, enabling the search of both a wider portion of the electromagnetic spectrum and a larger area of the sky.

With more data than ever on distant systems and the potential for life there, we spoke to Andrew Siemion, director of the Berkeley SETI Research Center and the Bernard M. Oliver Chair for SETI at the SETI Institute, about the leaps and bounds in the field of SETI enabled by new technologies and the rise of Big Data.

More data is a boon to researchers, but large amounts of data require large amounts of analysis. SETI has often made use of cutting edge technologies and approaches to fuel its ambitious search, and researchers have embraced the public’s interest in the topic to recruit them as citizen scientists. Citizen scientists have contributed to major findings in the field such as identifying Tabby’s Star from Kepler telescope data, a star with unusually fluctuating brightness which some theorized could be due to the presence of a civilization there.

“SETI is a remarkable draw for people,” Siemion said. “Anyone who looks up at the sky asks the question, ‘Is there anybody out there?’ That’s a very natural, very human question to ask. The scientists who work in this field have the same innate curiosity about the universe as the general public does. It’s a great draw and a great way to get people interested [in science].”

In 1999, the SETI@home project invited the public to contribute computing resources to the analysis of SETI data in one of the earliest distributed computing projects. This approach has now been expanded to other fields such as modeling parts of our galaxy and searching for gravitational waves, and distributed computing is even being used to search for a treatment for COVID-19.

The SETI@home project set a new standard for citizen science and engaging the public in astronomy research, however, the project was shut down this year after 20 years of analyzing data. One of the reasons for this bittersweet closing of the project was, counter-intuitively, that there is now actually too much data to comb through. Telescopes generate more data than ever and are usually in remote locations with internet connections no fast than a gigabit per second. The logistics of distributing data over such connections made the project inefficient.

“The telescopes are now capable of producing so much data that it’s not possible to get that volume of data out to volunteers,” Siemion explained. “The discovery space is in these massive, massive data streams. And it’s just not efficient to distribute many terabits per second out to volunteers all over the world. It’s more efficient for that data processing to happen at the actual observatory.”

Now, instead of distributed computing projects, one area that SETI scientists want to include the public in is supervised machine learning, in which people are asked to identify or group features in images using a website they can access from home. Citizen scientists are currently participating in similar projects to analyze light pollution or to find driving routes for rovers on Mars.

This approach could be useful in SETI too, as Siemion described: “How can we leverage human beings’ natural ability to identify clusters of features in images, for example?” This could involve asking the public to analyze images of the sky, or getting them to analyze spectrograms, which are visual representations of radio telescope data. Having SETI data labeled or categorized means it can be analyzed much more efficiently.

However, one of the challenges in recruiting the public for SETI is that the kinds of analysis which are done often require highly specialized knowledge. Not everyone has the skills to analyze complex data or to create software. Fortunately, citizen scientists come in many different forms, from the casual member of the public who has just heard about an astronomy finding in the news and would like to help for a few hours, to someone who has a job such as a machine learning engineer and wants to volunteer their skills to contribute to a software project.

There’s value in getting contributions from all of these people with their different skill sets. “We try to address the citizen scientists at many different levels,” Siemion said. “We try to find something for everybody, so that there are ways for lots of different people with lots of different experience levels and technical expertise to engage in the projects that we have.”

Interest in SETI can be used to bring the public into science as well. A recent collaboration between the SETI Institute and the open-source software project GNU Radio aims to give people the opportunity to learn about radio engineering, digital signal processing, and radio astronomy. By purchasing a dongle for around $25, members of the public can digitize analog radio signals and process signals on their computers.

“GNU Radio is very interesting because these devices are very inexpensive and through experimenting with software-defined radio, people can develop a lot of very important skills for the kinds of work we do, particularly in radio SETI,” Siemion said. “For all intents and purposes, these [dongles] are a micro version of the million-dollar digital computing systems that we attach to radio telescopes.”

This kind of collaboration not only teaches people about science and engineering, but it also broadens the pool of expertise around radio engineering, which can feed back into new techniques and knowledge which will help SETI projects in the future.

Siemion says he’s given hope for the bright future of SETI indicated by the recent finding of a potential biomarker for life on Venus. “It’s still just a hint, the phosphene detection, but it’s a beautiful hint,” Siemion said.

“It’s incredibly exciting and heartening to see discoveries like this, and very motivating. Just as the discovery of the ubiquity of extrasolar planets has motivated the search for life, I think that the discovery of a biosignature will take things to another level yet.”

Editors' Recommendations