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Secretive agency uses AI, human 'forecasters' to predict the future
A U.S. government intelligence agency develops cutting-edge tech to predict future events.
- The Intelligence Advanced Research Projects Activity (IARPA), a research arm of the U.S. government intelligence community, is focused on predicting the future.
- The organization uses teams of human non-experts and AI machine learning to forecast future events.
- IARPA also conducts advanced research in numerous other fields, funding rotating programs.
As far as secretive government projects go, the objectives of IARPA may be the riskiest and most far-reaching. With its mission to foster "high-risk, high-payoff" programs, this research arm of the U.S. intelligence community literally tries to predict the future. Staffed by spies and Ph.D.s, this organization aims to provide decision makers with real, accurate predictions of geopolitical events, using artificial intelligence and human "forecasters."
IARPA, which stands for Intelligence Advanced Research Projects Activity, was founded in 2006 as part of the Office of the Director of National Intelligence. Some of the projects that it has funded focused on advancements in quantum computing, cryogenic computing, face recognition, universal language translators, and other initiatives that would fit well in a Hollywood action movie plot. But perhaps its main goal is to produce "anticipatory intelligence." It's a spy agency, after all.
"Minority report" pre-cog
Dreamworks/20th Century Fox
In the interest of national security, IARPA wants to identify major world events before they happen, looking for terrorists, hackers or any perceived enemies of the United States. Wouldn't you rather stop a crime before it happens?
Of course, that's when we get into tricky political and sci-fi territory. Much of the research done by IARPA is actually out in the open, utilizing the public and experts in advancing technologies. It is available for "open solicitations," forecasting tournaments, and has prize challenges for the public. You can pretty much send your idea in right now. But what happens to the R&D once it leaves the lab is, of course, often for only the NSA and the CIA to know.
The National Security Agency expert James Bamford wrote that the agency is ultimately looking to create a system where huge amounts of data about people's lives would be mined in real-time, for the purpose of preventing actions detrimental to the nation. In his article for the Pittsburgh Post-Gazette, Bamford wrote that IARPA's goal is to create very powerful automated computer systems, managed through artificial intelligence, which would be "capable of cataloging the lives of everyone everywhere, 24/ 7." Such programs would be able to instantaneously access data streams belonging to citizens, whether from social media or anywhere else. As Bamford writes, being able to analyze "every Facebook post, tweet and YouTube video; every tollbooth tag number; every GPS download, web search and news feed; every street camera video; every restaurant reservation on Open Table — largely eliminates surprise from the intelligence equation."
Of course, one would suspect much of this is going on already. IARPA's Mercury program, for example, concentrates on data mining millions of private overseas communications that are gathered by the National Security Agency. While it can certainly be argued that such a program is a national security necessity, working to spot terrorists and elements that can lead to social unrest, the potential for misuse and infringement on privacy rights has alerted observers.
A fascinating recent project funded by IARPA is called SAGE, which stands for Synergistic Anticipation of Geopolitical Events. As you may expect from such a lofty title, the researchers involved in this endeavor are looking to predict the future. This project is aimed at utilizing non-experts – humans who would use AI machine learning to make qualified statements about what would happen.
Led by Aram Galstyan, director of the Artificial Intelligence Division at the USC Viterbi Information Sciences Institute (ISI), the project has been successful in making concrete predictions, like knowing when North Korea would launch its missile tests. SAGE works by utilizing large sets of human non-expert predictors, pooling their powers by working together, making them "more accurate and faster than a single human subject expert," as explains a USC press release. However, the information these humans or "forecasters" use to make predictions is gathered through a variety of machine learning technologies.
The topics looked at by the predictors include such questions as "Will any G7 nation engage in an acknowledged national military attack against Syria [by a given date]?" They may also want to figure out exactly how much oil Venezuela might produce in a specific month.
Leaders among the forecasters, or those who make the most accurate predictions, are ranked and highlighted with badges.
This AI-assisted crowd-sourced Nostradamus has worked out quite well, according to Fred Morstatter, a USC computer scientist. "We believe that's the case because the numbers we're seeing indicate we are outpacing a system that uses only humans," he remarked.
SAGE's hybrid model functions by offering humans information derived by the machines in charts that show trends, along with specific predictions by the AI. "SAGE works because humans have one side of the coin, and machines have the other side," said Morstatter. And on yet another side you would have the National Intelligence apparatus.
Do you have a good idea for future-oriented national security research? You can actually apply to be a IARPA program manager. Current managers, who rotate every 3 to 5 years, are working on a vast variety of fields, including forecasting, linguistics, underwater technology, aerospace propulsion, atomic physics, artificial intelligence, biometrics, neuroscience, and optics. Check out the list of existing programs.
Northwell Health is using insights from website traffic to forecast COVID-19 hospitalizations two weeks in the future.
- The machine-learning algorithm works by analyzing the online behavior of visitors to the Northwell Health website and comparing that data to future COVID-19 hospitalizations.
- The tool, which uses anonymized data, has so far predicted hospitalizations with an accuracy rate of 80 percent.
- Machine-learning tools are helping health-care professionals worldwide better constrain and treat COVID-19.
The value of forecasting<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTA0Njk2OC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMzM2NDQzOH0.rid9regiDaKczCCKBsu7wrHkNQ64Vz_XcOEZIzAhzgM/img.jpg?width=980" id="2bb93" class="rm-shortcode" data-rm-shortcode-id="31345afbdf2bd408fd3e9f31520c445a" data-rm-shortcode-name="rebelmouse-image" data-width="1546" data-height="1056" />
Northwell emergency departments use the dashboard to monitor in real time.
Credit: Northwell Health<p>One unique benefit of forecasting COVID-19 hospitalizations is that it allows health systems to better prepare, manage and allocate resources. For example, if the tool forecasted a surge in COVID-19 hospitalizations in two weeks, Northwell Health could begin:</p><ul><li>Making space for an influx of patients</li><li>Moving personal protective equipment to where it's most needed</li><li>Strategically allocating staff during the predicted surge</li><li>Increasing the number of tests offered to asymptomatic patients</li></ul><p>The health-care field is increasingly using machine learning. It's already helping doctors develop <a href="https://care.diabetesjournals.org/content/early/2020/06/09/dc19-1870" target="_blank">personalized care plans for diabetes patients</a>, improving cancer screening techniques, and enabling mental health professionals to better predict which patients are at <a href="https://healthitanalytics.com/news/ehr-data-fuels-accurate-predictive-analytics-for-suicide-risk" target="_blank" rel="noopener noreferrer">elevated risk of suicide</a>, to name a few applications.</p><p>Health systems around the world have already begun exploring how <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315944/" target="_blank" rel="noopener noreferrer">machine learning can help battle the pandemic</a>, including better COVID-19 screening, diagnosis, contact tracing, and drug and vaccine development.</p><p>Cruzen said these kinds of tools represent a shift in how health systems can tackle a wide variety of problems.</p><p>"Health care has always used the past to predict the future, but not in this mathematical way," Cruzen said. "I think [Northwell Health's new predictive tool] really is a great first example of how we should be attacking a lot of things as we go forward."</p>
Making machine-learning tools openly accessible<p>Northwell Health has made its predictive tool <a href="https://github.com/northwell-health/covid-web-data-predictor" target="_blank">available for free</a> to any health system that wishes to utilize it.</p><p>"COVID is everybody's problem, and I think developing tools that can be used to help others is sort of why people go into health care," Dr. Cruzen said. "It was really consistent with our mission."</p><p>Open collaboration is something the world's governments and health systems should be striving for during the pandemic, said Michael Dowling, Northwell Health's president and CEO.</p><p>"Whenever you develop anything and somebody else gets it, they improve it and they continue to make it better," Dowling said. "As a country, we lack data. I believe very, very strongly that we should have been and should be now working with other countries, including China, including the European Union, including England and others to figure out how to develop a health surveillance system so you can anticipate way in advance when these things are going to occur."</p><p>In all, Northwell Health has treated more than 112,000 COVID patients. During the pandemic, Dowling said he's seen an outpouring of goodwill, collaboration, and sacrifice from the community and the tens of thousands of staff who work across Northwell.</p><p>"COVID has changed our perspective on everything—and not just those of us in health care, because it has disrupted everybody's life," Dowling said. "It has demonstrated the value of community, how we help one another."</p>
"You dream about these kinds of moments when you're a kid," said lead paleontologist David Schmidt.
- The triceratops skull was first discovered in 2019, but was excavated over the summer of 2020.
- It was discovered in the South Dakota Badlands, an area where the Triceratops roamed some 66 million years ago.
- Studying dinosaurs helps scientists better understand the evolution of all life on Earth.
Credit: David Schmidt / Westminster College<p style="margin-left: 20px;">"We had to be really careful," Schmidt told St. Louis Public Radio. "We couldn't disturb anything at all, because at that point, it was under law enforcement investigation. They were telling us, 'Don't even make footprints,' and I was thinking, 'How are we supposed to do that?'"</p><p>Another difficulty was the mammoth size of the skull: about 7 feet long and more than 3,000 pounds. (For context, the largest triceratops skull ever unearthed was about <a href="https://www.tandfonline.com/doi/abs/10.1080/02724634.2010.483632" target="_blank">8.2 feet long</a>.) The skull of Schmidt's dinosaur was likely a <em>Triceratops prorsus, </em>one of two species of triceratops that roamed what's now North America about 66 million years ago.</p>
Credit: David Schmidt / Westminster College<p>The triceratops was an herbivore, but it was also a favorite meal of the T<em>yrannosaurus rex</em>. That probably explains why the Dakotas contain many scattered triceratops bone fragments, and, less commonly, complete bones and skulls. In summer 2019, for example, a separate team on a dig in North Dakota made <a href="https://www.nytimes.com/2019/07/26/science/triceratops-skull-65-million-years-old.html" target="_blank">headlines</a> after unearthing a complete triceratops skull that measured five feet in length.</p><p>Michael Kjelland, a biology professor who participated in that excavation, said digging up the dinosaur was like completing a "multi-piece, 3-D jigsaw puzzle" that required "engineering that rivaled SpaceX," he jokingly told the <a href="https://www.nytimes.com/2019/07/26/science/triceratops-skull-65-million-years-old.html" target="_blank">New York Times</a>.</p>
Morrison Formation in Colorado
James St. John via Flickr
|Credit: Nobu Tamura/Wikimedia Commons|
Archaeologists discover a cave painting of a wild pig that is now the world's oldest dated work of representational art.
- Archaeologists find a cave painting of a wild pig that is at least 45,500 years old.
- The painting is the earliest known work of representational art.
- The discovery was made in a remote valley on the Indonesian island of Sulawesi.
Oldest Cave Art Found in Sulawesi<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="a9734e306f0914bfdcbe79a1e317a7f0"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/b-wAYtBxn7E?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span>
The Persian polymath and philosopher of the Islamic Golden Age teaches us about self-awareness.