The Algorithm Will See You Now
There's a quiet revolution going on in medicine. It's driven by artificial intelligence, but paradoxically, new technology may put a more human face on healthcare.
AI's usefulness in healthcare ranges far and wide.
Artificial intelligence is software that can process massive amounts of information and learn over time, arriving at decisions with striking accuracy and efficiency. It offers greater accuracy in diagnosis, exponentially faster genome sequencing, the mining of medical literature and patient records at breathtaking speed, a dramatic reduction in administrative bureaucracy, personalized medicine, and even the democratization of healthcare.
The algorithms that bring these advantages won't replace doctors; rather, by offloading some of the most time-consuming tasks in healthcare, providers will be able to focus on personal interactions with patients—listening, empathizing, educating and generally putting the care back in healthcare. The relationship can focus on the alleviation of suffering, both the physical and emotional kind.
Challenges of Getting AI Up and Running
The AI revolution, still in its early phase in medicine, is already spurring some amazing advances, despite the fact that some experts say it has been overhyped. IBM's Watson Health program is a case in point. IBM capitalized on Watson's ability to process natural language by designing algorithms that devour data like medical articles and analyze images like MRIs and medical slides. The algorithms help diagnose diseases and recommend treatment strategies.
But Technology Review reported that a heavily hyped partnership with the MD Anderson Cancer Center in Houston fell apart in 2017 because of a lack of data in the proper format. The data existed, just not in a way that the voraciously data-hungry AI could use to train itself.
The hiccup certainly hasn't dampened the enthusiasm for medical AI among other tech giants, including Google and Apple, both of which have invested billions in their own healthcare projects. At this point, the main challenge is the need for algorithms to interpret a huge diversity of data mined from medical records. This can include everything from CT scans, MRIs, electrocardiograms, x-rays, and medical slides, to millions of pages of medical literature, physician's notes, and patient histories. It can even include data from implantables and wearables such as the Apple Watch and blood sugar monitors.
None of this information is in anything resembling a standard format across and even within hospitals, clinics, and diagnostic centers. Once the algorithms are trained, however, they can crunch massive amounts of data at blinding speed, with an accuracy that matches and sometimes even exceeds that of highly experienced doctors.
Genome sequencing, for example, took years to accomplish as recently as the early 2000s. The Human Genome Project, the first sequencing of the human genome, was an international effort that took 13 years to complete. In April of this year, Rady Children's Institute for Genomic Medicine in San Diego used an AI-powered genome sequencing algorithm to diagnose rare genetic diseases in infants in about 20 hours, according to ScienceDaily.
"Patient care will always begin and end with the doctor."
Dr. Stephen Kingsmore, the lead author of an article published in Science Translational Medicine, emphasized that even though the algorithm helped guide the treatment strategies of neonatal intensive care physicians, the doctor was still an indispensable link in the chain. "Some people call this artificial intelligence, we call it augmented intelligence," he says. "Patient care will always begin and end with the doctor."
One existing trend is helping to supply a great amount of valuable data to algorithms—the electronic health record. Initially blamed for exacerbating the already crushing workload of many physicians, the EHR is emerging as a boon for algorithms because it consolidates all of a patient's data in one record.
Examples of AI in Action Around the Globe
If you're a parent who has ever taken a child to the doctor with flulike symptoms, you know the anxiety of wondering if the symptoms signal something serious. Kang Zhang, M.D., Ph.D., the founding director of the Institute for Genomic Medicine at the University of California at San Diego, and colleagues developed an AI natural language processing model that used deep learning to analyze the EHRs of 1.3 million pediatric visits to a clinic in Guanzhou, China.
The AI identified common childhood diseases with about the same accuracy as human doctors, and it was even able to split the diagnoses into two categories—common conditions such as flu, and serious, life-threatening conditions like meningitis. Zhang has emphasized that the algorithm didn't replace the human doctor, but it did streamline the diagnostic process and could be used in a triage capacity when emergency room personnel need to prioritize the seriously ill over those suffering from common, less dangerous ailments.
AI's usefulness in healthcare ranges far and wide. In Uganda and several other African nations, AI is bringing modern diagnostics to remote villages that have no access to traditional technologies such as x-rays. The New York Times recently reported that there, doctors are using a pocket-sized, hand-held ultrasound machine that works in concert with a cell phone to image and diagnose everything from pneumonia (a common killer of children) to cancerous tumors.
The beauty of the highly portable, battery-powered device is that ultrasound images can be uploaded on computers so that physicians anywhere in the world can review them and weigh in with their advice. And the images are instantly incorporated into the patient's EHR.
Jonathan Rothberg, the founder of Butterfly Network, the Connecticut company that makes the device, told The New York Times that "Two thirds of the world's population gets no imaging at all. When you put something on a chip, the price goes down and you democratize it." The Butterfly ultrasound machine, which sells for $2,000, promises to be a game-changer in remote areas of Africa, South America, and Asia, as well as at the bedsides of patients in developed countries.
AI algorithms are rapidly emerging in healthcare across the U.S. and the world. China has become a major international player, set to surpass the U.S. this year in AI capital investment, the translation of AI research into marketable products, and even the number of often-cited research papers on AI. So far the U.S. is still the leader, but some experts describe the relationship between the U.S. and China as an AI cold war.
"The future of machine learning isn't sentient killer robots. It's longer human lives."
The U.S. Food and Drug Administration expanded its approval of medical algorithms from two in all of 2017 to about two per month throughout 2018. One of the first fields to be impacted is ophthalmology.
One algorithm, developed by the British AI company DeepMind (owned by Alphabet, the parent company of Google), instantly scans patients' retinas and is able to diagnose diabetic retinopathy without needing an ophthalmologist to interpret the scans. This means diabetics can get the test every year from their family physician without having to see a specialist. The Financial Times reported in March that the technology is now being used in clinics throughout Europe.
In Copenhagen, emergency service dispatchers are using a new voice-processing AI called Corti to analyze the conversations in emergency phone calls. The algorithm analyzes the verbal cues of callers, searches its huge database of medical information, and provides dispatchers with onscreen diagnostic information. Freddy Lippert, the CEO of EMS Copenhagen, notes that the algorithm has already saved lives by expediting accurate diagnoses in high-pressure situations where time is of the essence.
Researchers at the University of Nottingham in the UK have even developed a deep learning algorithm that predicts death more accurately than human clinicians. The algorithm incorporates data from a huge range of factors in a chronically ill population, including how many fruits and vegetables a patient eats on a daily basis. Dr. Stephen Weng, lead author of the study, published in PLOS ONE, said in a press release, "We found machine learning algorithms were significantly more accurate in predicting death than the standard prediction models developed by a human expert."
New digital technologies are allowing patients to participate in their healthcare as never before. A feature of the new Apple Watch is an app that detects cardiac arrhythmias and even produces an electrocardiogram if an abnormality is detected. The technology, approved by the FDA, is helping cardiologists monitor heart patients and design interventions for those who may be at higher risk of a cardiac event like a stroke.
If having an algorithm predict your death sends a shiver down your spine, consider that algorithms may keep you alive longer. In 2018, technology reporter Tristan Greene wrote for Medium that "…despite the unending deluge of panic-ridden articles declaring AI the path to apocalypse, we're now living in a world where algorithms save lives every day. The future of machine learning isn't sentient killer robots. It's longer human lives."
The Risks of AI Compiling Your Data
To be sure, the advent of AI-infused medical technology is not without its risks. One risk is that the use of AI wearables constantly monitoring our vital signs could turn us into a nation of hypochondriacs, racing to our doctors every time there's a blip in some vital sign. Such a development could stress an already overburdened system that suffers from, among other things, a shortage of doctors and nurses. Another risk has to do with the privacy protections on the massive repository of intimately personal information that AI will have on us.
In an article recently published in the Journal of the American Medical Association, Australian researcher Kit Huckvale and colleagues examined the handling of data by 36 smartphone apps that assisted people with either depression or smoking cessation, two areas that could lend themselves to stigmatization if they fell into the wrong hands.
Out of the 36 apps, 33 shared their data with third parties, despite the fact that just 25 of those apps had a privacy policy at all and out of those, only 23 stated that data would be shared with third parties. The recipients of all that data? It went almost exclusively to Facebook and Google, to be used for advertising and marketing purposes. But there's nothing to stop it from ending up in the hands of insurers, background databases, or any other entity.
Even when data isn't voluntarily shared, any digital information can be hacked. EHRs and even wearable devices share the same vulnerability as any other digital record or device. Still, the promise of AI to radically improve efficiency and accuracy in healthcare is hard to ignore.
AI Can Help Restore Humanity to Medicine
Eric Topol, director of the Scripps Research Translational Institute and author of the new book Deep Medicine, says that AI gives doctors and nurses the most precious gift of all: time.
Topol welcomes his patients' use of the Apple Watch cardiac feature and is optimistic about the ways that AI is revolutionizing medicine. He says that the watch helps doctors monitor how well medications are working and has already helped to prevent strokes. But in addition to that, AI will help bring the humanity back to a profession that has become as cold and hard as a stainless steel dissection table.
"When I graduated from medical school in the 1970s," he says, "you had a really intimate relationship with your doctor." Over the decades, he has seen that relationship steadily erode as medical organizations demanded that doctors see more and more patients within ever-shrinking time windows.
"Doctors have no time to think, to communicate. We need to restore the mission in medicine."
In addition to that, EHRs have meant that doctors and nurses are getting buried in paperwork and administrative tasks. This is no doubt one reason why a recent study by the World Health Organization showed that worldwide, about 50 percent of doctors suffer from burnout. People who are utterly exhausted make more mistakes, and medical clinicians are no different from the rest of us. Only medical mistakes have unacceptably high stakes. According to its website, Johns Hopkins University recently announced that in the U.S. alone, 250,000 people die from medical mistakes each year.
"Doctors have no time to think, to communicate," says Topol. "We need to restore the mission in medicine." AI is giving doctors more time to devote to the thing that attracted them to medicine in the first place—connecting deeply with patients.
There is a real danger at this juncture, though, that administrators aware of the time-saving aspects of AI will simply push doctors to see more patients, read more tests, and embrace an even more crushing workload.
"We can't leave it to the administrators to just make things worse," says Topol. "Now is the time for doctors to advocate for a restoration of the human touch. We need to stand up for patients and for the patient-doctor relationship."
AI could indeed be a game changer, he says, but rather than squander the huge benefits of more time, "We need a new equation going forward."
In the 1990s, a mysterious virus spread throughout the Massachusetts Institute of Technology Artificial Intelligence Lab—or that’s what the scientists who worked there thought. More of them rubbed their aching forearms and massaged their cricked necks as new computers were introduced to the AI Lab on a floor-by-floor basis. They realized their musculoskeletal issues coincided with the arrival of these new computers—some of which were mounted high up on lab benches in awkward positions—and the hours spent typing on them.
Today, these injuries have become more common in a society awash with smart devices, sleek computers, and other gadgets. And we don’t just get hurt from typing on desktop computers; we’re massaging our sore wrists from hours of texting and Facetiming on phones, especially as they get bigger in size.
In 2007, the first iPhone measured 3.5-inches diagonally, a measurement known as the display size. That’s been nearly doubled by the newest iPhone 13 Pro, which has a 6.7-inch display. Other phones, too, like the Google Pixel 6 and the Samsung Galaxy S22, have bigger screens than their predecessors. Physical therapists and orthopedic surgeons have had to come up with names for a variety of new conditions: selfie elbow, tech neck, texting thumb. Orthopedic surgeon Sonya Sloan says she sees selfie elbow in younger kids and in women more often than men. She hears complaints related to technology once or twice a day.
The addictive quality of smartphones and social media means that people spend more time on their devices, which exacerbates injuries. According to Statista, 68 percent of those surveyed spent over three hours a day on their phone, and almost half spent five to six hours a day. Another report showed that people dedicate a third of their day to checking their phones, while the Media Effects Research Laboratory at Pennsylvania State University has found that bigger screens, ideal for entertainment purposes, immerse their users more than smaller screens. Oversized screens also provide easier navigation and more space for those with bigger hands or trouble seeing.
But others with conditions like arthritis can benefit from smaller phones. In March of 2016, Apple released the iPhone SE with a display size of 4.7 inches—an inch smaller than the iPhone 7, released that September. Apple has since come out with two more versions of the diminutive iPhone SE, one in 2020 and another in 2022.
These devices are now an inextricable part of our lives. So where does the burden of responsibility lie? Is it with consumers to adjust body positioning, get ergonomic workstations, and change habits to abate tech-related pain? Or should tech companies be held accountable?
Kavin Senapathy, a freelance science journalist, has the Google Pixel 6. She was drawn to the phone because Google marketed the Pixel 6’s camera as better at capturing different skin tones. But this phone boasts one of the largest display sizes on the market: 6.4 inches.
Senapathy was diagnosed with carpal and cubital tunnel syndromes in 2017 and fibromyalgia in 2019. She has had to create a curated ergonomic workplace setup, otherwise her wrists and hands get weak and tingly, and she’s had to adjust how she holds her phone to prevent pain flares.
Recently, Senapathy underwent an electromyography, or an EMG, in which doctors insert electrodes into muscles to measure their electrical activity. The electrical response of the muscles tells doctors whether the nerve cells and muscles are successfully communicating. Depending on her results, steroid shots and even surgery might be required. Senapathy wants to stick with her Pixel 6, but the pain she’s experiencing may push her to buy a smaller phone. Unfortunately, options for these modestly sized phones are more limited.
These devices are now an inextricable part of our lives. So where does the burden of responsibility lie? Is it with consumers like Senapathy to adjust body positioning, get ergonomic workstations, and change habits to abate tech-related pain? Or should tech companies be held accountable for creating addictive devices that lead to musculoskeletal injury?
Kavin Senapathy, a freelance journalist, bought the Google Pixel 6 because of its high-quality camera, but she’s had to adjust how she holds the oversized phone to prevent pain flares.
Kavin Senapathy
A one-size-fits-all mentality for smartphones will continue to lead to injuries because every user has different wants and needs. S. Shyam Sundar, the founder of Penn State’s lab on media effects and a communications professor, says the needs for mobility and portability conflict with the desire for greater visibility. “The best thing a company can do is offer different sizes,” he says.
Joanna Bryson, an AI ethics expert and professor at The Hertie School of Governance in Berlin, Germany, echoed these sentiments. “A lot of the lack of choice we see comes from the fact that the markets have consolidated so much,” she says. “We want to make sure there’s sufficient diversity [of products].”
Consumers can still maintain some control despite the ubiquity of tech. Sloan, the orthopedic surgeon, has to pester her son to change his body positioning when using his tablet. Our heads get heavier as they bend forward: at rest, they weigh 12 pounds, but bent 60 degrees, they weigh 60. “I have to tell him, ‘Raise your head, son!’” she says. It’s important, Sloan explains, to consider that growth and development will affect ligaments and bones in the neck, potentially making kids even more vulnerable to injuries from misusing gadgets. She recommends that parents limit their kids’ tech time to alleviate strain. She also suggested that tech companies implement a timer to remind us to change our body positioning.
In 2017, Nan-Wei Gong, a former contractor for Google, founded Figur8, which uses wearable trackers to measure muscle function and joint movement. It’s like physical therapy with biofeedback. “Each unique injury has a different biomarker,” says Gong. “With Figur8, you are comparing yourself to yourself.” This allows an individual to self-monitor for wear and tear and strengthen an injury in a way that’s efficient and designed for their body. Gong noticed that the work-from-home model during the COVID-19 pandemic created a new set of ergonomic problems that resulted in injuries. Figur8 provides real-time data for these injuries because “behavioral change requires feedback.”
Gong worked on a project called Jacquard while at Google. Textile experts weave conductive thread into their fabric, and the result is a patch of the fabric—like the cuff of a Levi’s jacket—that responds to commands on your smartphone. One swipe can call your partner or check the weather. It was designed with cyclists in mind who can’t easily check their phones, and it’s part of a growing movement in the tech industry to deliver creative, hands-free design. Gong thinks that engineers at large corporations like Google have accessibility in mind; it’s part of what drives their decisions for new products.
Display sizes of iPhones have become larger over time.
Sourced from Screenrant https://screenrant.com/iphone-apple-release-chronological-order-smartphone/ and Apple Tech Specs: https://www.apple.com/iphone-se/specs/
Back in Germany, Joanna Bryson reminds us that products like smartphones should adhere to best practices. These rules may be especially important for phones and other products with AI that are addictive. Disclosure, accountability, and regulation are important for AI, she says. “The correct balance will keep changing. But we have responsibilities and obligations to each other.” She was on an AI Ethics Council at Google, but the committee was disbanded after only one week due to issues with one of their members.
Bryson was upset about the Council’s dissolution but has faith that other regulatory bodies will prevail. OECD.AI, and international nonprofit, has drafted policies to regulate AI, which countries can sign and implement. “As of July 2021, 46 governments have adhered to the AI principles,” their website reads.
Sundar, the media effects professor, also directs Penn State’s Center for Socially Responsible AI. He says that inclusivity is a crucial aspect of social responsibility and how devices using AI are designed. “We have to go beyond first designing technologies and then making them accessible,” he says. “Instead, we should be considering the issues potentially faced by all different kinds of users before even designing them.”
Jessica Ware is obsessed with bugs.
My guest today is a leading researcher on insects, the president of the Entomological Society of America and a curator at the American Museum of Natural History. Learn more about her here.
You may not think that insects and human health go hand-in-hand, but as Jessica makes clear, they’re closely related. A lot of people care about their health, and the health of other creatures on the planet, and the health of the planet itself, but researchers like Jessica are studying another thing we should be focusing on even more: how these seemingly separate areas are deeply entwined. (This is the theme of an upcoming event hosted by Leaps.org and the Aspen Institute.)
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Entomologist Jessica Ware
D. Finnin / AMNH
Maybe it feels like a core human instinct to demonize bugs as gross. We seem to try to eradicate them in every way possible, whether that’s with poison, or getting out our blood thirst by stomping them whenever they creep and crawl into sight.
But where did our fear of bugs really come from? Jessica makes a compelling case that a lot of it is cultural, rather than in-born, and we should be following the lead of other cultures that have learned to live with and appreciate bugs.
The truth is that a healthy planet depends on insects. You may feel stung by that news if you hate bugs. Reality bites.
Jessica and I talk about whether learning to live with insects should include eating them and gene editing them so they don’t transmit viruses. She also tells me about her important research into using genomic tools to track bugs in the wild to figure out why and how we’ve lost 50 percent of the insect population since 1970 according to some estimates – bad news because the ecosystems that make up the planet heavily depend on insects. Jessica is leading the way to better understand what’s causing these declines in order to start reversing these trends to save the insects and to save ourselves.