The Inquiry Committee, which receives comments from a multitude of small panels, takes into account a gargantuan amount of information to create research strategies. While the Academies won’t release the committee’s final recommendation to NASA for a few weeks, scientists are eager to see which of their questions will be taken up and which will be left out.

“The Decadal Investigation really helps NASA decide how it is going to lead the future of human discovery in space, so it’s very important that it is well informed,” says Brant Robertson, professor of astronomy and astrophysics at UC Santa Cruz.

A team of researchers want to use artificial intelligence to facilitate this process. Their proposal is not for a specific mission or line of questioning; rather, they say, their AI can help scientists make tough decisions about which other proposals to prioritize.

The idea is that by training an AI to spot areas of research that are either growing or declining rapidly, the tool could make it easier for committees of inquiry and panels to decide what should be on the list. .

“What we wanted was to have a system that would do a lot of the work done by the ten-year survey and let the scientists working on the ten-year survey do what they would do best,” explains Harley thronson, retired senior scientist at NASA’s Goddard Space Flight Center and lead author of the proposal.

Although the members of each committee are chosen for their expertise in their respective fields, it is impossible for each member to grasp the nuance of each scientific theme. The number of publications in astrophysics increases by 5% each year, according to the authors. It’s a lot to deal with for anyone.

This is where Thronson’s AI comes in.

It took a little over a year to build, but ultimately the Thronson team was able to train them on over 400,000 pieces of research published in the decade leading up to the Astro2010 investigation. They were also able to teach AI to sift through thousands of summaries to identify high and low impact areas from two and three word thematic phrases like “planetary system” or “extrasolar planet”.

According to the researchers’ white paper, AI has managed to “backcast” six popular research themes of the past 10 years, including a meteoric rise in exoplanet research and galaxy observation.

“One of the difficult aspects of artificial intelligence is that it will sometimes predict, propose or analyze things that are completely surprising to humans,” says Thronson. “And we’ve seen that a lot. ”

Thronson and colleagues believe the steering committee should use their AI to help review and summarize the vast amounts of text the panel must sift through, leaving human experts to make the final call.

Their research is not the first to try to use AI to analyze and shape scientific literature. Other AIs have already been used to help scientists peer review work of their colleagues.

But could it be entrusted with a task as important and influential as the Decennial Inquiry?



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