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.
14 January, 2021
Credit: Getty Images
- 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.
<p>One of the most devastating aspects of the COVID-19 pandemic has been unpredictability. The nation's health systems—especially those in hard-hit areas like New York City—have had to adapt to sudden surges of COVID-19 cases, all while dealing with limited resources, existing patients, and a novel virus that's still not fully understood.</p><p>But what if health systems were able to forecast COVID-19 hospitalizations two weeks before they occur? Northwell Health, the largest health care system in New York state, recently deployed a predictive tool that does just that.</p><p>Northwell Health's <a href="https://www.northwell.edu/northwell-website-patterns-predict-covid-19-cases" target="_blank">surveillance dashboard</a> is able to predict COVID-19 hospitalizations by using insights from machine learning. In March, Northwell Health's Customer Insights Group developed an algorithm that's been mining data from online traffic to the Northwell.edu website, which has received more than 20 million hits since March.<strong></strong></p><p>The algorithm collects data through 15 different indicators, each of which reflects the online behavior of the website's visitors. For example, the tool analyzes metrics such as the length of time users spend on certain pages, searches for emergency department wait times, and specific symptoms users search for. Combined, this information translates into something like the "public mood" of the website on any given day.</p>
<blockquote>Since Northwell Health began using the predictive tool in September, it's predicted COVID-19 hospitalizations with an accuracy of about 80 percent.</blockquote>
<p>To understand how this mood relates to future COVID-19 cases, Northwell Health began comparing its data with a timeline of COVID-19 hospitalizations across 23 hospitals and nearly 800 outpatient facilities and in the metro New York area. This enabled the Customer Insights Group to see patterns of online activity that precede future increases or decreases in hospitalizations.</p><p>Since Northwell Health began using the predictive tool in September, it's predicted COVID-19 hospitalizations with an accuracy of about 80 percent.</p><p>"This is really the first tool that I've been exposed to that gives me a sort of guestimate of what two weeks from now may look like," said Dr. <a href="https://www.northwell.edu/find-care/find-a-doctor/emergency-medicine/dr-eric-scott-cruzen-md-mba-11346068" target="_blank" rel="noopener noreferrer">Eric Cruzen, </a>chief medical informatics officer of Northwell's emergency medicine services and chair of the emergency department at Lenox Health Greenwich Village in Manhattan.</p><p>"Even if the data can provide an idea of whether to expect an increase, decrease, or stasis, that's valuable. Because every day we're working to estimate what tomorrow's going to bring. Any tool that's going to shed light on that is a good tool in my book."</p>
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>
Keep reading
Show less
5 of the most amazing cracked codes in modern history
From 260-year-old ciphers to the most recent Zodiac Killer solution, these unbreakable codes just needed time.
16 December, 2020
- After 51 years, the Zodiac Killer's infamous "340 code" has been solved.
- Humans have a natural passion for puzzles, making cryptography a lifelong pursuit for some.
- Other famous cracked codes include Poe's Challenge and Zimmermann's Letter.
<p>Humans love puzzles. Thanks to an evolutionary skillset that lets us piece together fragments of information necessary for survival, we've turned biological instinct into a love for games. Sometimes our affection manifests in Candy Crush; other times, in solving uncrackable ciphers.</p><p>Numerous unbreakable codes persist. The CIA awaits the brave thinker that will crack the fourth code in its <a href="https://www.newscientist.com/article/mg21028133-800-unbreakable-kryptos-a-monument-to-cia-secrecy/" target="_blank">Kryptos monument</a>. The <a href="https://www.mentalfloss.com/article/540277/beale-ciphers-buried-treasure" target="_blank" rel="noopener noreferrer">Beale ciphers</a> may or may not reveal $60 million in hidden treasure. Composer Edward Elgar continues to <a href="http://nautil.us/issue/6/secret-codes/the-artist-of-the-unbreakable-code" target="_blank" rel="noopener noreferrer">laugh from beyond the grave</a>. </p><p>Few codes stand the test of time, however. It took nearly 600 years for researchers to realize the <a href="https://arstechnica.com/science/2017/09/the-mysterious-voynich-manuscript-has-finally-been-decoded/" target="_blank" rel="noopener noreferrer">Voynich manuscript</a> was effectively a rip-off copy of Women's Health. The <a href="https://www.wired.com/story/a-programmer-solved-a-20-year-old-forgotten-crypto-puzzle/" target="_blank" rel="noopener noreferrer">MIT time-lock puzzle</a> was only 20 years old, yet it still took a nifty programmer three years to crack it. And then there's the Zodiac Killer. </p>The recent news that a 51-year-old letter from the infamous Bay Area murderer, whose story was <a href="https://www.netflix.com/title/70044686" target="_blank" rel="noopener noreferrer">immortalized by David Fincher</a>, has been cracked recently made headlines. While this code will bring no peace to the families of the unknown killer's victims, the solving of this letter reminds us once again that nothing is impenetrable.
How I cracked the Zodiac Killer's cipher
<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="d0b8a7170b77210c07cfad50b99ef328"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/3sLFRm29eto?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span><h2>Zodiac Killer</h2><p>After the Zodiac Killer's first cryptogram was quickly solved in 1969, he followed up with a 340-character puzzle that has baffled cryptographers ever since. Three men worked tirelessly on the letter and <a href="https://www.wired.com/story/zodiac-killers-cipher-finally-cracked-after-51-years/" target="_blank" rel="noopener noreferrer">finally revealed the encoded message</a>: </p><p>I HOPE YOU ARE HAVING LOTS OF FUN IN TRYING TO CATCH ME THAT WASN'T ME ON THE TV SHOW WHICH BRINGS UP A POINT ABOUT ME I AM NOT AFRAID OF THE GAS CHAMBER BECAUSE IT WILL SEND ME TO PARADICE ALL THE SOONER BECAUSE I NOW HAVE ENOUGH SLAVES TO WORK FOR ME WHERE EVERYONE ELSE HAS NOTHING WHEN THEY REACH PARADICE SO THEY ARE AFRAID OF DEATH I AM NOT AFRAID BECAUSE I KNOW THAT MY NEW LIFE WILL BE AN EASY ONE IN PARADICE DEATH</p><p>While the San Francisco branch of the FBI has acknowledged the puzzle has been solved, they're not providing any more comments considering the case remains open. </p><h2>Poe's Challenge </h2><p>Edgar Allan Poe's "The Gold Bug" was based on a cipher mystery, as Poe himself was fascinated with puzzles. In 1840, he offered a free subscription to Graham's Magazine to anyone who could stump him. He claims to have solved a hundred entries, ending the contest by publishing a challenging code written by W.B. Tyler—who many at the time suspected was a pseudonym.</p><p>It wasn't until 2000 that a <a href="https://www.scientificamerican.com/article/a-cipher-from-poe-solved/" target="_blank" rel="noopener noreferrer">software engineer decoded the message</a>, which opened up, "It was early spring, warm and sultry glowed the afternoon. The very breezes seemed to share the delicious languor of universal nature..."</p><p>Given the numerous typesetting mistakes, recent researchers aren't convinced that Poe actually wrote it. The author will likely remain a mystery, but the code itself is in the books. </p><h2>Copiale cipher</h2><p>An entire team spanning two countries was needed to crack the 260-year-old mystery of the <a href="https://cl.lingfil.uu.se/~bea/copiale/" target="_blank" rel="noopener noreferrer">Copiale cipher</a>. Unlike a few lines of prose, this 75,000-character manuscript filled 105 pages written by a group of ophthalmologists. The book was encrypted in German and relied on a complex substitution code that used symbols and letters for spaces as well as text. </p><p>Dating from the second half of the eighteenth century, the first 16 pages discuss a masonic initiation ceremony by the Oculists. The strange ritual involves initiates "reading" a blank piece of paper before being given a pair of glasses—those wily eye doctors. After their eyes are washed, the referees then pluck a single eyebrow of each recruit. </p><p>Better than college hazing, though still an odd text to keep so secretive. Then again, maybe that was the point. </p><img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNDk2NTM5NC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTY1NjM0NTE4M30.Ai2W0qq46YG7u5iTIhcgGciX20GahtlaeGK74r4Jzao/img.jpg?width=980" id="a34a1" class="rm-shortcode" data-rm-shortcode-id="72011ca823bf25dfadafb177196b4410" data-rm-shortcode-name="rebelmouse-image" data-width="2000" data-height="1502" />
Slate statue of Mathematician Alan Turing at Bletchley Park
Credit: lenscap50 / Adobe Stock
<h2>The Zimmermann Telegram</h2><p>Not all codes are so playful, or strange. Some are insidious. Such is the case with the <a href="https://www.history.com/news/what-was-the-zimmermann-telegram" target="_blank" rel="noopener noreferrer">Zimmermann Telegram</a>, a note sent from Germany to Mexico in 1917. Intended for the German ambassador to Mexico, Heinrich von Eckardt, the Germans were preparing America's southern neighbors for battle—in the name of Germany. In exchange for weapons and funding, the Mexicans would reclaim Arizona, New Mexico, and Texas upon victory. </p><p>The cipher was cracked about a month after interception by Britain's "Room 40." The text read, in part:</p><p style="margin-left: 20px;">"We make Mexico a proposal of alliance on the following basis: make war together, make peace together, generous financial support and an understanding on our part that Mexico is to reconquer the lost territory in Texas, New Mexico, and Arizona. The settlement in detail is left to you."</p><p>Tensions between the US and Germany were already high; this message pushed America over the edge. A month later, President Wilson overruled his intention of remaining neutral and entered World War I on the side of the Allies. </p><h2>The Enigma Code </h2><p>One of the most famous cracks in history is certainly the <a href="https://www.iwm.org.uk/history/how-alan-turing-cracked-the-enigma-code" target="_blank" rel="noopener noreferrer">Enigma Code</a>. If the Zimmermann Telegram helped us get into World War I, the second chapter only ended in our favor thanks to Alan Turing's unforgettable machine. </p><p>The Germans were utilizing an enciphering machine to pass messages to its Axis partners. Perhaps learning from past mistakes, they changed the entire cipher system on a daily basis. </p><p>Turing responded with his own machinery: the Bombe, Lorenz, and Universal Turing Machine. Thanks to his inventions, alongside tireless efforts by British cryptologists, the Allied forces exploited procedural flaws and operator mistakes by the Germans. The Enigma Code was cracked, saving countless Allied lives and helping turn the tide of the war. </p><p>--</p><p><em>Stay in touch with Derek on <a href="http://www.twitter.com/derekberes" target="_blank">Twitter</a> and <a href="https://www.facebook.com/DerekBeresdotcom" target="_blank" rel="noopener noreferrer">Facebook</a>. His new book is</em> "<em><a href="https://www.amazon.com/gp/product/B08KRVMP2M?pf_rd_r=MDJW43337675SZ0X00FH&pf_rd_p=edaba0ee-c2fe-4124-9f5d-b31d6b1bfbee" target="_blank" rel="noopener noreferrer">Hero's Dose: The Case For Psychedelics in Ritual and Therapy</a>."</em></p>
Keep reading
Show less
Crazy dreams help us make sense of our memories
A new theory suggests that dreams' illogical logic has an important purpose.
17 November, 2020
Credit: Paul Fleet/Adobe Stock
<ul class="ee-ul"></ul><p><br></p>
<p class=""><br></p>
<p>For a while now, the leading theory about what we're doing when we dream is that we're sorting through our experiences of the last day or so, consolidating some stuff into memories for long-term storage, and discarding the rest. That doesn't explain, though, why our dreams are so often so exquisitely weird.</p><p>A new theory proposes our brains toss in all that crazy as a way of helping us process our daily experiences, much in the way that programmers add unrelated, random-ish nonsense, or "noise," into machine learning data sets to help computers discern useful, predictive patterns in the data they're fed.</p>
Overfitting
<p>The goal of machine learning is to supply an algorithm with a data set, a "training set," in which patterns can be recognized and from which predictions that apply to other unseen data sets can be derived.</p><p>If machine learning learns its training set too well, it merely spits out a prediction that precisely — and uselessly — matches that data instead of underlying patterns within it that could serve as predictions likely to be true of other thus-far unseen data. In such a case, the algorithm describes what the data set <em>is</em> rather than what it <em>means</em>. This is called "overfitting."</p><img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNDc4NTQ4Ni9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTY2NDM4NDk1Mn0.bMHbBbt7Nz0vmmQ8fdBKaO-Ycpme5eOCxbjPLEHq9XQ/img.jpg?width=980" id="5049a" class="rm-shortcode" data-rm-shortcode-id="f9a6823125e01f4d69ce13d1eef84486" data-rm-shortcode-name="rebelmouse-image" data-width="1440" data-height="585" />Big Think
The value of noise
<p>To keep machine learning from becoming too fixated on the specific data points in the set being analyzed, programmers may introduce extra, unrelated data as noise or corrupted inputs that are less self-similar than the real data being analyzed.</p><p>This noise typically has nothing to do with the project at hand. It's there, metaphorically speaking, to "distract" and even confuse the algorithm, forcing it to step back a bit to a vantage point at which patterns in the data may be more readily perceived and not drawn from the specific details within the data set.</p><p>Unfortunately, overfitting also occurs a lot in the real world as people race to draw conclusions from insufficient data points — xkcd has a fun example of how this can happen with <a href="https://xkcd.com/1122/" target="_blank">election "facts."</a></p><p>(In machine learning, there's also "underfitting," where an algorithm is too simple to track enough aspects of the data set to glean its patterns.)</p><img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNDc4NTQ5My9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMDE5NjY1M30.iS2bq7WEQLeS34zNFPnXwzAZZn9blCyI-KVuXmcHI6o/img.jpg?width=980" id="cd486" class="rm-shortcode" data-rm-shortcode-id="c49cfbbffceb00e3f37f00e0fef859d9" data-rm-shortcode-name="rebelmouse-image" data-width="1440" data-height="810" />Credit: agsandrew/Adobe Stock
Nightly noise
<p>There remains a lot we don't know about how much storage space our noggins contain. However, it's obvious that if the brain remembered absolutely everything we experienced in every detail, that would be an awful lot to remember. So it seems the brain consolidates experiences as we dream. To do this, it must make sense of them. It must have a system for figuring out what's important enough to remember and what's unimportant enough to forget rather than just dumping the whole thing into our long-term memory.</p><p>Performing such a wholesale dump would be an awful lot like overfitting: simply documenting what we've experienced without sorting through it to ascertain its meaning.</p><p>This is where the new theory, the <a href="https://arxiv.org/pdf/2007.09560.pdf" target="_blank">Overfitting Brain Hypothesis</a> (OBH) proposed by Erik Hoel of Tufts University, comes in. Suggesting that perhaps the brain's sleeping analysis of experiences is akin to machine learning, he proposes that the illogical narratives in dreams are the biological equivalent of the noise programmers inject into algorithms to keep them from overfitting their data. He says that this may supply just enough off-pattern nonsense to force our brains to see the forest and not the trees in our daily data, our experiences.</p><p>Our experiences, of course, are delivered to us as sensory input, so Hoel suggests that dreams are sensory-input noise, biologically-realistic noise injection with a narrative twist:</p><p style="margin-left: 20px;">"Specifically, there is good evidence that dreams are based on the stochastic percolation of signals through the hierarchical structure of the cortex, activating the default-mode network. Note that there is growing evidence that most of these signals originate in a top-down manner, meaning that the 'corrupted inputs' will bear statistical similarities to the models and representations of the brain. In other words, they are derived from a stochastic exploration of the hierarchical structure of the brain. This leads to the kind structured hallucinations that are common during dreams."</p><p>Put plainly, our dreams are just realistic enough to engross us and carry us along, but are just different enough from our experiences —our "training set" — to effectively serve as noise.</p><p>It's an interesting theory.</p><p>Obviously, we don't know the extent to which our biological mental process actually resemble the comparatively simpler, man-made machine learning. Still, the OBH is worth thinking about, maybe at least more worth thinking about than whatever <em>that</em> was last night.</p>
Keep reading
Show less
The Matrix is already here: Social media promised to connect us, but left us isolated, scared and tribal
The more you like, follow and share, the faster you find yourself moving in that political direction.
12 November, 2020
Photo by Dan LeFebvre on Unsplash
About a year ago I began to follow my interest in health and fitness on Instagram. Soon I began to see more and more fitness-related accounts, groups, posts and ads.
<p> I kept clicking and following, and eventually my Instagram became all about fit people, fitness and motivational material, and advertisements. Does this sound familiar?</p><p>While the algorithms and my brain kept me scrolling on the endless feeds, I was reminded of what digital marketers like to say: “Money is in the list." That is, the more customized your group, people and page follows, the less time and money is needed to sell you related ideas. Instead, brand ambassadors will do the work, spreading products, ideas and ideologies with passion and free of charge. </p><p><a href="https://www.starclab.org/members/arash-javanbakht" target="_blank">I'm a psychiatrist</a> who studies anxiety and stress, and I often write about how our politics and culture are mired in fear and tribalism. <a href="https://www.linkedin.com/in/marina-arakcheieva-57850916/" target="_blank">My co-author</a> is a digital marketing expert who brings expertise to the technological-psychological aspect of this discussion. With the nation on edge, we believe it's critical to look at how easily our society is being manipulated into tribalism in the age of social media. Even after the exhausting election cycle is over, the division persists, if not widening, and conspiracy theories continue to emerge, grow and divide on the social media. Based on our knowledge of stress, fear and social media, we offer you some ways to weather the next few days, and protect yourself against the current divisive environment.</p>
<h2>The promise, the Matrix</h2><p>Those of us old enough to know what life was like before social media may remember how exciting Facebook was at its inception. Imagine, the ability to connect with old friends we had not seen for decades! Then, Facebook was a virtual dynamic conversation. This brilliant idea, to connect to others with shared experiences and interests, was strengthened with the advent of Twitter, Instagram and apps.</p><p>Things did not remain that simple. These platforms have morphed into Frankenstein's monsters, filled with so-called friends we've never met, slanted news stories, celebrity gossip, self-aggrandizement and ads.</p><p>The artificial intelligence behind these platforms determines what you see based on your social media and web activity, including <a href="https://www.facebook.com/ds/preferences/" target="_blank" rel="noopener noreferrer">your engagement</a> with pages and ads. For example, on Twitter you may follow the politicians you like. Twitter algorithms quickly respond and show you more posts and people related to that political leaning. The more you like, follow and share, the faster you find yourself moving in that political direction. There is, however, this nuance: Those algorithms tracking you are often triggered by your <a href="https://theconversation.com/the-science-of-fright-why-we-love-to-be-scared-85885" target="_blank" rel="noopener noreferrer">negative emotions</a>, typically impulsivity or anger.</p><p>As a result, <a href="https://www.youtube.com/watch?v=kc_Jq42Og7Q&fbclid=IwAR0rdHWlYYnBmmxVwTD36JZ__HQfaU9BcgifDNFuG4stTLLyQvykIh5cvNo" target="_blank" rel="noopener noreferrer">the algorithms</a> amplify the negative and then spread it by sharing it among groups. This might play a role in the widespread anger among those engaged in politics, regardless of their side of the aisle.</p>
<h2>The digital tribe</h2><p>Eventually, the algorithms expose us mostly to the ideology of one "digital tribe" – the same way my Instagram world became only superfit and active people. This is how one's Matrix can become the extremes of conservatism, liberalism, different religions, climate change worriers or deniers or other ideologies. Members of each tribe keep consuming and feeding one another the same ideology while policing one another against opening up to "the others."</p><p>We are inherently tribal creatures anyway; but particularly when we're scared, we regress further into tribalism and tend to trust the information relayed to us by our tribe and not by others. Normally, that's <a href="https://theconversation.com/trump-the-politics-of-fear-and-racism-how-our-brains-can-be-manipulated-to-tribalism-139811" target="_blank" rel="noopener noreferrer">an evolutionary advantage</a>. Trust leads to group cohesion, and it helps us survive.</p><p>But now, that same tribalism – along with peer pressure, negative emotions and short tempers – often lead to ostracizing those who disagree with you. <a href="https://civicscience.com/the-majority-of-americans-are-also-social-distancing-from-politics/" target="_blank" rel="noopener noreferrer">In one study</a>, 61% of Americans reported having unfriended, unfollowed or blocked someone on social media because of their political views or posts.</p><p>Higher levels of social media use and exposure to sensationalized news about the pandemic is linked with <a href="https://pubmed.ncbi.nlm.nih.gov/32945123/" target="_blank" rel="noopener noreferrer">increased depression and stress</a>. And more time spent on social media correlates with <a href="https://pubmed.ncbi.nlm.nih.gov/27723539/" target="_blank" rel="noopener noreferrer">higher anxiety</a>, which can create a negative loop. <a href="https://www.journalism.org/2020/10/07/before-trump-tested-positive-for-coronavirus-republicans-attention-to-pandemic-had-sharply-declined/" target="_blank" rel="noopener noreferrer">One example</a>: The Pew Research Center reports 90% of Republicans who get their political news only from conservative platforms said the U.S. has controlled the COVID-19 outbreak as much as possible. Yet less than half of Republicans who rely on at least one other major news provider thought so.</p>
<h2>The Matrix does the thinking</h2><p>Human thinking itself has been transformed. It's now more difficult for us to grasp the "big picture." A book is a long read these days, too much for some people. Scrolling and swiping culture has reduced our attention span (on average people spend <a href="https://www.facebook.com/business/news/insights/capturing-attention-feed-video-creative" target="_blank" rel="noopener noreferrer">1.7 to 2.5 seconds</a> on a Facebook news feed item). It has also deactivated our critical thinking skills. Even really big news doesn't last on our feed longer than a few hours; after all, the next blockbuster story is just ahead. The Matrix does the thinking; we consume the ideology and are bolstered by the likes from our tribemates.</p><p>Before all this, our social exposure was mostly to family, friends, relatives, neighbors, classmates, TV, movies, radio, newspapers, magazines and books. And that was enough. In that, there was diversity and a relatively healthy information diet with a wide variety of nutrients. We always knew people who were not like minded, but getting along with them was normal life, part of the deal. Now those different voices have become more distant – "the others" we love to hate on social media.</p>
<h2>Is there a red pill?</h2><p>We need to take back the control. Here are seven things we can do to unplug ourselves out of the Matrix:</p><ul><li>Review and update <a href="https://www.facebook.com/ds/preferences/" target="_blank" rel="noopener noreferrer">your ad preferences</a> on social media at least once per year.</li><li>Confuse the AI by flagging all ads and suggestions as "irrelevant."</li><li>Practice being more inclusive. Check other websites, read their news and do not "unfriend" people who think differently from you.</li><li>Turn off cable news and read instead. Or at least put a disciplined limit on hours of exposure.</li><li>Check out less biased sources of news such as <a href="https://www.npr.org/" target="_blank" rel="noopener noreferrer">NPR</a>, <a href="https://www.bbc.com/" target="_blank" rel="noopener noreferrer">BBC</a> and <a href="https://theconversation.com/us" target="_blank" rel="noopener noreferrer">The Conversation</a>.</li><li>If you think everything your tribe leaders say is absolute truth, think again.</li><li>Go offline and go out (just wear your mask). Practice smartphone-free hours.</li><li>Finally, remember that your neighbor who supports the other football team or the other political party <a href="https://twitter.com/JoeBiden/status/1324926298762870785?s=20" target="_blank" rel="noopener noreferrer">is not your enemy</a>; you can still go for a bike ride together! I did today, and we didn't even have to talk politics.</li></ul><p>It's time to take the red pill. Take these seven steps, and you won't give in to the Matrix.</p><p><em>This piece was co-authored with Maryna Arakcheieva, who is expert in digital solutions and marketing</em>.<img src="https://counter.theconversation.com/content/148799/count.gif?distributor=republish-lightbox-basic" alt="The Conversation"></p><p><a href="https://theconversation.com/profiles/arash-javanbakht-416594" target="_blank">Arash Javanbakht</a>, Associate Professor of Psychiatry, <em><a href="https://theconversation.com/institutions/wayne-state-university-989" target="_blank" rel="noopener noreferrer">Wayne State University</a></em></p><p>This article is republished from <a href="https://theconversation.com/" target="_blank" rel="noopener noreferrer">The Conversation</a> under a Creative Commons license. Read the <a href="https://theconversation.com/the-matrix-is-already-here-social-media-promised-to-connect-us-but-left-us-isolated-scared-and-tribal-148799" target="_blank" rel="noopener noreferrer">original article</a>.</p>
Keep reading
Show less
Catching serial killers with an algorithm
This week, Big Think is partnering with Freethink to bring you amazing stories of the people and technologies that are shaping our future.
07 October, 2020
- There are over 250,000 unsolved murder cases in the United States. Thomas Hargrove, cofounder of Murder Accountability Project, wants that number to be as close to zero as possible, and he has just the tool to help.
- Hargrove developed an algorithm that, through cluster analysis, is capable of finding connections in murder data that human investigators tend to miss.
- The technology exists, but a considerable roadblock that the project faces is getting support and cooperation from law enforcement offices.
<p><br></p><p class="shortcode-media shortcode-media-rebelmouse-image">
<a href="https://www.youtube.com/channel/UConJDkGk921yT9hISzFqpzw?sub_confirmation=1" target="_blank"><img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNDQ2MzQyNS9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYxMTQwOTA3NX0.rXGXbzof1ph8fRnrmGpq4cys1YizZqWZD71E1e-Sp0w/img.jpg?width=980" id="0a0d0" class="rm-shortcode" data-rm-shortcode-id="d8f806065b0d82ef2e333d4d550e36e7" data-rm-shortcode-name="rebelmouse-image" alt=""></a>
<small class="image-media media-photo-credit" placeholder="add photo credit..."><a href="https://www.youtube.com/channel/UConJDkGk921yT9hISzFqpzw?sub_confirmation=1" target="_blank"></a></small>
</p><p>At Big Think, we share actionable lessons from the world's greatest thinkers and doers. This week, we're partnering with <a href="https://www.youtube.com/channel/UConJDkGk921yT9hISzFqpzw?sub_confirmation=1" rel="noopener noreferrer" target="_blank">Freethink</a> to bring you amazing stories of the people and technologies that are shaping our future, from neuroscience breakthroughs to bionics and justice. Catch Freethink's documentary-style videos here and on our YouTube channel this Monday, Wednesday, and Friday.</p>
Keep reading
Show less
Popular
