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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.
How New York's largest hospital system is predicting COVID-19 spikes
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>Listen: Scientists re-create voice of 3,000-year-old Egyptian mummy
Scientists used CT scanning and 3D-printing technology to re-create the voice of Nesyamun, an ancient Egyptian priest.
- Scientists printed a 3D replica of the vocal tract of Nesyamun, an Egyptian priest whose mummified corpse has been on display in the UK for two centuries.
- With the help of an electronic device, the reproduced voice is able to "speak" a vowel noise.
- The team behind the "Voices of the Past" project suggest reproducing ancient voices could make museum experiences more dynamic.
Howard et al.
<p style="margin-left: 20px;">"While this approach has wide implications for heritage management/museum display, its relevance conforms exactly to the ancient Egyptians' fundamental belief that 'to speak the name of the dead is to make them live again'," they wrote in a <a href="https://www.nature.com/articles/s41598-019-56316-y#Fig3" target="_blank">paper</a> published in Nature Scientific Reports. "Given Nesyamun's stated desire to have his voice heard in the afterlife in order to live forever, the fulfilment of his beliefs through the synthesis of his vocal function allows us to make direct contact with ancient Egypt by listening to a sound from a vocal tract that has not been heard for over 3000 years, preserved through mummification and now restored through this new technique."</p>Connecting modern people with history
<p>It's not the first time scientists have "re-created" an ancient human's voice. In 2016, for example, Italian researchers used software to <a href="https://www.smithsonianmag.com/smart-news/hear-recreated-voice-otzi-iceman-180960570/" target="_blank">reconstruct the voice of Ötzi,</a> an iceman who was discovered in 1991 and is thought to have died more than 5,000 years ago. But the "Voices of the Past" project is different, the researchers note, because Nesyamun's mummified corpse is especially well preserved.</p><p style="margin-left: 20px;">"It was particularly suited, given its age and preservation [of its soft tissues], which is unusual," Howard told <em><a href="https://www.livescience.com/amp/ancient-egypt-mummy-voice-reconstructed.html" target="_blank">Live Science</a>.</em></p><p>As to whether Nesyamun's reconstructed voice will ever be able to speak complete sentences, Howard told <em><a href="https://abcnews.go.com/Weird/wireStory/ancient-voice-scientists-recreate-sound-egyptian-mummy-68482015" target="_blank">The Associated Press</a>, </em>that it's "something that is being worked on, so it will be possible one day."</p><p>John Schofield, an archaeologist at the University of York, said that reproducing voices from history can make museum experiences "more multidimensional."</p><p style="margin-left: 20px;">"There is nothing more personal than someone's voice," he told <em>The Associated Press.</em> "So we think that hearing a voice from so long ago will be an unforgettable experience, making heritage places like Karnak, Nesyamun's temple, come alive."</p>Dark matter axions possibly found near Magnificent 7 neutron stars
A new study proposes mysterious axions may be found in X-rays coming from a cluster of neutron stars.
A rendering of the XMM-Newton (X-ray multi-mirror mission) space telescope.
Are Axions Dark Matter?
<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="5e35ce24a5b17102bfce5ae6aecc7c14"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/e7yXqF32Yvw?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span>Put on a happy face? “Deep acting” associated with improved work life
New research suggests you can't fake your emotional state to improve your work life — you have to feel it.
What is deep acting?
<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTQ1NDk2OS9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYxNTY5MzA0Nn0._s7aP25Es1CInq51pbzGrUj3GtOIRWBHZxCBFnbyXY8/img.jpg?width=1245&coordinates=333%2C-1%2C333%2C-1&height=700" id="ddf09" class="rm-shortcode" data-rm-shortcode-id="9dc42c4d6a8e372ad7b72907b46ecd3f" data-rm-shortcode-name="rebelmouse-image" data-width="1245" data-height="700" />Arlie Russell Hochschild (pictured) laid out the concept of emotional labor in her 1983 book, "The Managed Heart."
Credit: Wikimedia Commons
<p>Deep and surface acting are the principal components of emotional labor, a buzz phrase you have likely seen flitting about the Twittersphere. Today, "<a href="https://www.bbc.co.uk/bbcthree/article/5ea9f140-f722-4214-bb57-8b84f9418a7e" target="_blank">emotional labor</a>" has been adopted by groups as diverse as family counselors, academic feminists, and corporate CEOs, and each has redefined it with a patented spin. But while the phrase has splintered into a smorgasbord of pop-psychological arguments, its initial usage was more specific.</p><p>First coined by sociologist Arlie Russell Hochschild in her 1983 book, "<a href="https://www.ucpress.edu/book/9780520272941/the-managed-heart" target="_blank">The Managed Heart</a>," emotional labor describes the work we do to regulate our emotions on the job. Hochschild's go-to example is the flight attendant, who is tasked with being "nicer than natural" to enhance the customer experience. While at work, flight attendants are expected to smile and be exceedingly helpful even if they are wrestling with personal issues, the passengers are rude, and that one kid just upchucked down the center aisle. Hochschild's counterpart to the flight attendant is the bill collector, who must instead be "nastier than natural."</p><p>Such personas may serve an organization's mission or commercial interests, but if they cause emotional dissonance, they can potentially lead to high emotional costs for the employee—bringing us back to deep and surface acting.</p><p>Deep acting is the process by which people modify their emotions to match their expected role. Deep actors still encounter the negative emotions, but they devise ways to <a href="http://www.selfinjury.bctr.cornell.edu/perch/resources/what-is-emotion-regulationsinfo-brief.pdf" target="_blank">regulate those emotions</a> and return to the desired state. Flight attendants may modify their internal state by talking through harsh emotions (say, with a coworker), focusing on life's benefits (next stop Paris!), physically expressing their desired emotion (smiling and deep breaths), or recontextualizing an inauspicious situation (not the kid's fault he got sick).</p><p>Conversely, surface acting occurs when employees display ersatz emotions to match those expected by their role. These actors are the waiters who smile despite being crushed by the stress of a dinner rush. They are the CEOs who wear a confident swagger despite feelings of inauthenticity. And they are the bouncers who must maintain a steely edge despite humming show tunes in their heart of hearts.</p><p>As we'll see in the research, surface acting can degrade our mental well-being. This deterioration can be especially true of people who must contend with negative emotions or situations inside while displaying an elated mood outside. Hochschild argues such emotional labor can lead to exhaustion and self-estrangement—that is, surface actors erect a bulwark against anger, fear, and stress, but that disconnect estranges them from the emotions that allow them to connect with others and live fulfilling lives.</p>Don't fake it till you make it
<p>Most studies on emotional labor have focused on customer service for the obvious reason that such jobs prescribe emotional states—service with a smile or, if you're in the bouncing business, a scowl. But <a href="https://eller.arizona.edu/people/allison-s-gabriel" target="_blank">Allison Gabriel</a>, associate professor of management and organizations at the University of Arizona's Eller College of Management, wanted to explore how employees used emotional labor strategies in their intra-office interactions and which strategies proved most beneficial.</p><p>"What we wanted to know is whether people choose to engage in emotion regulation when interacting with their co-workers, why they choose to regulate their emotions if there is no formal rule requiring them to do so, and what benefits, if any, they get out of this effort," Gabriel said in <a href="https://www.sciencedaily.com/releases/2020/01/200117162703.htm" target="_blank">a press release</a>.</p><p>Across three studies, she and her colleagues surveyed more than 2,500 full-time employees on their emotional regulation with coworkers. The survey asked participants to agree or disagree with statements such as "I try to experience the emotions that I show to my coworkers" or "I fake a good mood when interacting with my coworkers." Other statements gauged the outcomes of such strategies—for example, "I feel emotionally drained at work." Participants were drawn from industries as varied as education, engineering, and financial services.</p><p>The results, <a href="https://psycnet.apa.org/doiLanding?doi=10.1037%2Fapl0000473" target="_blank" rel="noopener noreferrer">published in the Journal of Applied Psychology</a>, revealed four different emotional strategies. "Deep actors" engaged in high levels of deep acting; "low actors" leaned more heavily on surface acting. Meanwhile, "non-actors" engaged in negligible amounts of emotional labor, while "regulators" switched between both. The survey also revealed two drivers for such strategies: prosocial and impression management motives. The former aimed to cultivate positive relationships, the latter to present a positive front.</p><p>The researchers found deep actors were driven by prosocial motives and enjoyed advantages from their strategy of choice. These actors reported lower levels of fatigue, fewer feelings of inauthenticity, improved coworker trust, and advanced progress toward career goals. </p><p>As Gabriel told <a href="https://www.psypost.org/2021/01/new-psychology-research-suggests-deep-acting-can-reduce-fatigue-and-improve-your-work-life-59081" target="_blank" rel="noopener noreferrer">PsyPost in an interview</a>: "So, it's a win-win-win in terms of feeling good, performing well, and having positive coworker interactions."</p><p>Non-actors did not report the emotional exhaustion of their low-actor peers, but they also didn't enjoy the social gains of the deep actors. Finally, the regulators showed that the flip-flopping between surface and deep acting drained emotional reserves and strained office relationships.</p><p>"I think the 'fake it until you make it' idea suggests a survival tactic at work," Gabriel noted. "Maybe plastering on a smile to simply get out of an interaction is easier in the short run, but long term, it will undermine efforts to improve your health and the relationships you have at work. </p><p>"It all boils down to, 'Let's be nice to each other.' Not only will people feel better, but people's performance and social relationships can also improve."</p>You'll be glad ya' decided to smile
<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="88a0a6a8d1c1abfcf7b1aca8e71247c6"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/QOSgpq9EGSw?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span><p>But as with any research that relies on self-reported data, there are confounders here to untangle. Even during anonymous studies, participants may select socially acceptable answers over honest ones. They may further interpret their goal progress and coworker interactions more favorably than is accurate. And certain work conditions may not produce the same effects, such as toxic work environments or those that require employees to project negative emotions.</p><p>There also remains the question of the causal mechanism. If surface acting—or switching between surface and deep acting—is more mentally taxing than genuinely feeling an emotion, then what physiological process causes this fatigue? <a href="https://www.frontiersin.org/articles/10.3389/fnhum.2019.00151/full" target="_blank">One study published in the <em>Frontiers in Human Neuroscience</em></a><em> </em>measured hemoglobin density in participants' brains using an fNIRS while they expressed emotions facially. The researchers found no significant difference in energy consumed in the prefrontal cortex by those asked to deep act or surface act (though, this study too is limited by a lack of real-life task).<br></p><p>With that said, Gabriel's studies reinforce much of the current research on emotional labor. <a href="https://journals.sagepub.com/doi/abs/10.1177/2041386611417746" target="_blank">A 2011 meta-analysis</a> found that "discordant emotional labor states" (read: surface acting) were associated with harmful effects on well-being and performance. The analysis found no such consequences for deep acting. <a href="https://doi.apa.org/doiLanding?doi=10.1037%2Fa0022876" target="_blank" rel="noopener noreferrer">Another meta-analysis</a> found an association between surface acting and impaired well-being, job attitudes, and performance outcomes. Conversely, deep acting was associated with improved emotional performance.</p><p>So, although there's still much to learn on the emotional labor front, it seems Van Dyke's advice to a Leigh was half correct. We should put on a happy face, but it will <a href="https://bigthink.com/design-for-good/everything-you-should-know-about-happiness-in-one-infographic" target="_self">only help if we can feel it</a>.</p>World's oldest work of art found in a hidden Indonesian valley
Archaeologists discover a cave painting of a wild pig that is now the world's oldest dated work of representational art.
