Big Data Probably Knows More About You Than Your Friends Do
Data is the new oil. It is highly valuable, and it is everywhere, even if you're not aware of it. For example, it's there when you use social media. Sharing pictures on Facebook lets its facial recognition software peg you and your friends. Thanks to that software, now anywhere you visit that has installed cameras, your face can be identified and your actions recorded.
The big data revolution is advancing much faster than the ones before, and it carries both promises and perils for humanity.
It's there when you log into Twitter, posting one of the 230 million tweets per day, which up until last month were all archived by the Library of Congress and will be made public for research. These social media data can be used to predict your political affiliations, ethnicity, race, age, how close you are with your family and friends, your mental health, even when you are most likely to be grumpy or go to the gym. These data can also predict when you are apt to get sick and track how diseases are spreading.
In fact, tracking isn't limited to what you decide to share or public spaces anymore. Lab experiments show Comcast and other cable companies may soon be able to record and monitor movements in your house. They may also be able to read your lips and identify your visitors simply by assessing how Wi-Fi waves bounce off bodies and other objects in houses. In one study, MIT researchers used routers and sensors to monitor breathing and heart rates with 99% accuracy. Routers could soon be used for seemingly good things, like monitoring infant breathing and whether an older adult is about to take a big tumble. However, it may also enable unwanted and unparalleled levels of surveillance.
Some call the first digital pill a snitch pill, medication with a tattletale, and big brother in your belly.
Big data is there every time you pick up your smartphone, which can track your daily steps, where you go via geolocation, what time you wake up and go to bed, your punctuality, and even your overall health depending on which features you have enabled. Are you close with your mom; are you a sedentary couch potato; did you commit a murder (iPhone data was recently used in a German murder trial)? Smartphone-generated data can be used to label you---and not just you, your future and past generations too.
Smartphones are not the only "things" gathering data on you. Anything with an on and off switch can be connected to the internet and generate data. The new rule seems to be, if it can be, it will be, connected. Washing machines, coffee makers, medical appliances, cars, and even your luggage (yes, someone created a self-driving suitcase) can and are often generating data. "Smart" refrigerators can monitor your food levels and automatically create shopping lists and order food for you—while recording your alcohol consumption and whether you tend to be a healthy or junk food eater.
Even medicines can monitor behaviors. The first digital pill was just approved by the FDA last November to track whether patients take their medicines. It has a sensor that sends signals to a patient's smartphone, and others, when it encounters stomach acid. Some call it a snitch pill, medication with a tattletale, and big brother in your belly. Others see it as a major breakthrough to help patients remember to take their medications and to save payers millions of dollars.
Big data is there when you go shopping. Credit card and retail data can show whether you pay for a gym, if you are pregnant, have children, and your credit-worthiness. Uber and Lyft transactional data reveal what time you usually go to and leave work and who you regularly visit (Uber data has been used to catch cheating spouses).
Amazon now sells a bedroom camera to see your fashion choices and offer advice. It is marketing a more fashionable you, but it probably also wants the video feed showing your body measurements—they're "a newly prized currency," according to the Washington Post. They help retailers create more customized and better fitting clothes. Amazon also just partnered with Berkshire Hathaway and JPMorgan Chase, the largest bank in the United States by assets, to create an independent health-care company for their employees--raising privacy concerns as Amazon already owns so much data about us, from drones, devices, the AI of Alexa, and our viewing, eating, and other purchasing habits on Amazon Prime.
Data generation and storage can also be used to make the world better, safer and fairer.
Big data is arguably a new phenomenon; almost all the world's data (90%) were produced within the last 2 years or so. It is a result of the fusion of physical, digital, and biological technologies that together constitute the fourth industrial revolution, according to the World Economic Forum. Unlike the last three revolutions, involving the discoveries of steam power, electrical energy, and computers—this revolution is advancing much faster than the ones before and it carries both promises and perils for humanity.
Some people may want to opt out of all this tracking, reduce their digital footprint and stay "off the grid." However, it is worth noting that data generation and storage can be used for great things --- things that make the world better, safer and fairer. For example, sharing electronic health records and social media data can help scientists better track and understand diseases, develop new cures and therapies, and understand the safety and efficacy profiles of medicines and vaccines.
While full of promise, big data is not without its pitfalls. Data are often not interoperable or easily integrated. You can use your credit card practically anywhere in the world, but you cannot easily port your electronic health record to the doctor or hospital across the street, for example.
Data quality can also be poor. It is dependent on the person entering it. My electronic health record at one point said I was male, and I was pregnant at the time. No doctors or nurses seemed to notice. The problem is worse on a global level. For example, causes of death can be coded differently by country and village. Take HIV patients: they often develop secondary infections, like TB. Do you record the cause of death as TB or HIV? There isn't global consistency, and political pressure from patient groups can exert itself on death records. Often, each group wants to say they have the most deaths so they can fundraise more money.
Data can be biased. More than 80 percent of genomic data comes from Caucasians. Only 14 percent is from Asians and 3.5 percent is from African and Hispanic populations. Thus, when scientists use genomic data to develop drugs or lab tests, they may create biased products that work for only some demographics. Take type 2 diabetes blood tests; some do not work well for African Americans. One study estimates that 650,000 African Americans may have undiagnosed diabetes, because a common blood test doesn't work for them. Using biased data in medicine can be a matter of life and death. Moreover, if genomic medicine benefits only "a privileged few," the practice raises concerns about unequal access.
Large companies are selling data that originated from you and you are not sharing in the wealth.
We need to think carefully and be transparent about the values embedded in our data, data analytics (algorithms), and data applications. Numbers are never neutral. Algorithms are always embedded with subjective normative values--sometimes purposely, sometimes not. To address this problem, we need ethicists who can audit databanks and algorithms to identify embedded norms, values and biases and help ensure they are addressed or at least transparently disclosed. Additionally, we need to determine how to let people opt out of certain types of data collection and uses—and not just at the beginning of a system, but also at any point in their lifetimes. There is a right to be forgotten, which hasn't been adequately operationalized in today's data sphere.
What do you think happens to all of these data collected about us? The short answer is the public doesn't really know. A lot of it looks like what is in a medical record—i.e. height, weight, pregnancy status, age, mental health, pulse, blood pressure, and illness symptoms--- yet, it isn't protected by HIPPA, like your medical record information.
And it is being consolidated into the hands of fewer and fewer big players. Large companies are selling data that originated from you and you are not sharing in the wealth.
A possible solution is to create an app, managed by a nonprofit or public benefit corporation, through which you could download and manage all the data collected about you. For example, you could download your credit card statements with all your purchasing habits, your Uber rides showing transit patterns, medical records, electric bills, every digital record you have and would like to download--into one application. You would then have the power to license pieces or the collection of your data to users for a small fee for one year at a time. Uses and users could be monitored and audited leveraging blockchain capabilities. After the year is up, you can withdraw access.
You could be your own data landlord. We could democratize big data and empower people to better control and manage the wealth of information collected about us. Why should only the big companies like Amazon and Apple profit off the new oil? Let's create an app so we can all manage our data wealth and maybe even become data barons—an app created by the people for the people.
A new injection is helping stave off RSV this season
In November 2021, Mickayla Wininger’s then one-month-old son, Malcolm, endured a terrifying bout with RSV, the respiratory syncytial (sin-SISH-uhl) virus—a common ailment that affects all age groups. Most people recover from mild, cold-like symptoms in a week or two, but RSV can be life-threatening in others, particularly infants.
Wininger, who lives in southern Illinois, was dressing Malcolm for bed when she noticed what seemed to be a minor irregularity with this breathing. She and her fiancé, Gavin McCullough, planned to take him to the hospital the next day. The matter became urgent when, in the morning, the boy’s breathing appeared to have stopped.
After they dialed 911, Malcolm started breathing again, but he ended up being hospitalized three times for RSV and defects in his heart. Eventually, he recovered fully from RSV, but “it was our worst nightmare coming to life,” Wininger recalled.
It’s a scenario that the federal government is taking steps to prevent. In July, the Food and Drug Administration approved a single-dose, long-acting injection to protect babies and toddlers. The injection, called Beyfortus, or nirsevimab, became available this October. It reduces the incidence of RSV in pre-term babies and other infants for their first RSV season. Children at highest risk for severe RSV are those who were born prematurely and have either chronic lung disease of prematurity or congenital heart disease. In those cases, RSV can progress to lower respiratory tract diseases such as pneumonia and bronchiolitis, or swelling of the lung’s small airway passages.
Each year, RSV is responsible for 2.1 million outpatient visits among children younger than five-years-old, 58,000 to 80,000 hospitalizations in this age group, and between 100 and 300 deaths, according to the Centers for Disease Control and Prevention. Transmitted through close contact with an infected person, the virus circulates on a seasonal basis in most regions of the country, typically emerging in the fall and peaking in the winter.
In August, however, the CDC issued a health advisory on a late-summer surge in severe cases of RSV among young children in Florida and Georgia. The agency predicts "increased RSV activity spreading north and west over the following two to three months.”
Infants are generally more susceptible to RSV than older people because their airways are very small, and their mechanisms to clear these passages are underdeveloped. RSV also causes mucus production and inflammation, which is more of a problem when the airway is smaller, said Jennifer Duchon, an associate professor of newborn medicine and pediatrics in the Icahn School of Medicine at Mount Sinai in New York.
In 2021 and 2022, RSV cases spiked, sending many to emergency departments. “RSV can cause serious disease in infants and some children and results in a large number of emergency department and physician office visits each year,” John Farley, director of the Office of Infectious Diseases in the FDA’s Center for Drug Evaluation and Research, said in a news release announcing the approval of the RSV drug. The decision “addresses the great need for products to help reduce the impact of RSV disease on children, families and the health care system.”
Sean O’Leary, chair of the committee on infectious diseases for the American Academy of Pediatrics, says that “we’ve never had a product like this for routine use in children, so this is very exciting news.” It is recommended for all kids under eight months old for their first RSV season. “I would encourage nirsevimab for all eligible children when it becomes available,” O’Leary said.
For those children at elevated risk of severe RSV and between the ages of 8 and 19 months, the CDC recommends one dose in their second RSV season.
The drug will be “really helpful to keep babies healthy and out of the hospital,” said O’Leary, a professor of pediatrics at the University of Colorado Anschutz Medical Campus/Children’s Hospital Colorado in Denver.
An antiviral drug called Synagis (palivizumab) has been an option to prevent serious RSV illness in high-risk infants since it was approved by the FDA in 1998. The injection must be given monthly during RSV season. However, its use is limited to “certain children considered at high risk for complications, does not help cure or treat children already suffering from serious RSV disease, and cannot prevent RSV infection,” according to the National Foundation for Infectious Diseases.
Until the approval this summer of the new monoclonal antibody, nirsevimab, there wasn’t a reliable method to prevent infection in most healthy infants.
Both nirsevimab and palivizumab are monoclonal antibodies that act against RSV. Monoclonal antibodies are lab-made proteins that mimic the immune system’s ability to fight off harmful pathogens such as viruses. A single intramuscular injection of nirsevimab preceding or during RSV season may provide protection.
The strategy with the new monoclonal antibody is “to extend protection to healthy infants who nonetheless are at risk because of their age, as well as infants with additional medical risk factors,” said Philippa Gordon, a pediatrician and infectious disease specialist in Brooklyn, New York, and medical adviser to Park Slope Parents, an online community support group.
No specific preventive measure is needed for older and healthier kids because they will develop active immunity, which is more durable. Meanwhile, older adults, who are also vulnerable to RSV, can receive one of two new vaccines. So can pregnant women, who pass on immunity to the fetus, Gordon said.
Until the approval this summer of the new monoclonal antibody, nirsevimab, there wasn’t a reliable method to prevent infection in most healthy infants, “nor is there any treatment other than giving oxygen or supportive care,” said Stanley Spinner, chief medical officer and vice president of Texas Children’s Pediatrics and Texas Children’s Urgent Care.
As with any virus, washing hands frequently and keeping infants and children away from sick people are the best defenses, Duchon said. This approach isn’t foolproof because viruses can run rampant in daycare centers, schools and parents’ workplaces, she added.
Mickayla Wininger, Malcolm’s mother, insists that family and friends wear masks, wash their hands and use hand sanitizer when they’re around her daughter and two sons. She doesn’t allow them to kiss or touch the children. Some people take it personally, but she would rather be safe than sorry.
Wininger recalls the severe anxiety caused by Malcolm's ordeal with RSV. After returning with her infant from his hospital stays, she was terrified to go to sleep. “My fiancé and I would trade shifts, so that someone was watching over our son 24 hours a day,” she said. “I was doing a night shift, so I would take caffeine pills to try and keep myself awake and would end up crashing early hours in the morning and wake up frantically thinking something happened to my son.”
Two years later, her anxiety has become more manageable, and Malcolm is doing well. “He is thriving now,” Wininger said. He recently had his second birthday and "is just the spunkiest boy you will ever meet. He looked death straight in the eyes and fought to be here today.”
Story by Big Think
For most of history, artificial intelligence (AI) has been relegated almost entirely to the realm of science fiction. Then, in late 2022, it burst into reality — seemingly out of nowhere — with the popular launch of ChatGPT, the generative AI chatbot that solves tricky problems, designs rockets, has deep conversations with users, and even aces the Bar exam.
But the truth is that before ChatGPT nabbed the public’s attention, AI was already here, and it was doing more important things than writing essays for lazy college students. Case in point: It was key to saving the lives of tens of millions of people.
AI-designed mRNA vaccines
As Dave Johnson, chief data and AI officer at Moderna, told MIT Technology Review‘s In Machines We Trust podcast in 2022, AI was integral to creating the company’s highly effective mRNA vaccine against COVID. Moderna and Pfizer/BioNTech’s mRNA vaccines collectively saved between 15 and 20 million lives, according to one estimate from 2022.
Johnson described how AI was hard at work at Moderna, well before COVID arose to infect billions. The pharmaceutical company focuses on finding mRNA therapies to fight off infectious disease, treat cancer, or thwart genetic illness, among other medical applications. Messenger RNA molecules are essentially molecular instructions for cells that tell them how to create specific proteins, which do everything from fighting infection, to catalyzing reactions, to relaying cellular messages.
Johnson and his team put AI and automated robots to work making lots of different mRNAs for scientists to experiment with. Moderna quickly went from making about 30 per month to more than one thousand. They then created AI algorithms to optimize mRNA to maximize protein production in the body — more bang for the biological buck.
For Johnson and his team’s next trick, they used AI to automate science, itself. Once Moderna’s scientists have an mRNA to experiment with, they do pre-clinical tests in the lab. They then pore over reams of data to see which mRNAs could progress to the next stage: animal trials. This process is long, repetitive, and soul-sucking — ill-suited to a creative scientist but great for a mindless AI algorithm. With scientists’ input, models were made to automate this tedious process.
“We don’t think about AI in the context of replacing humans,” says Dave Johnson, chief data and AI officer at Moderna. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
All these AI systems were in put in place over the past decade. Then COVID showed up. So when the genome sequence of the coronavirus was made public in January 2020, Moderna was off to the races pumping out and testing mRNAs that would tell cells how to manufacture the coronavirus’s spike protein so that the body’s immune system would recognize and destroy it. Within 42 days, the company had an mRNA vaccine ready to be tested in humans. It eventually went into hundreds of millions of arms.
Biotech harnesses the power of AI
Moderna is now turning its attention to other ailments that could be solved with mRNA, and the company is continuing to lean on AI. Scientists are still coming to Johnson with automation requests, which he happily obliges.
“We don’t think about AI in the context of replacing humans,” he told the Me, Myself, and AI podcast. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
Moderna, which was founded as a “digital biotech,” is undoubtedly the poster child of AI use in mRNA vaccines. Moderna recently signed a deal with IBM to use the company’s quantum computers as well as its proprietary generative AI, MoLFormer.
Moderna’s success is encouraging other companies to follow its example. In January, BioNTech, which partnered with Pfizer to make the other highly effective mRNA vaccine against COVID, acquired the company InstaDeep for $440 million to implement its machine learning AI across its mRNA medicine platform. And in May, Chinese technology giant Baidu announced an AI tool that designs super-optimized mRNA sequences in minutes. A nearly countless number of mRNA molecules can code for the same protein, but some are more stable and result in the production of more proteins. Baidu’s AI, called “LinearDesign,” finds these mRNAs. The company licensed the tool to French pharmaceutical company Sanofi.
Writing in the journal Accounts of Chemical Research in late 2021, Sebastian M. Castillo-Hair and Georg Seelig, computer engineers who focus on synthetic biology at the University of Washington, forecast that AI machine learning models will further accelerate the biotechnology research process, putting mRNA medicine into overdrive to the benefit of all.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.