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.
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."
You are driving along the highway and see an electronic sign that reads: “3,238 traffic deaths this year.” Do you think this reminder of roadside mortality would change how you drive? According to a recent, peer-reviewed study in Science, seeing that sign would make you more likely to crash. That’s ironic, given that the sign’s creators assumed it would make you safer.
The study, led by a pair of economists at the University of Toronto and University of Minnesota, examined seven years of traffic accident data from 880 electric highway sign locations in Texas, which experienced 4,480 fatalities in 2021. For one week of each month, the Texas Department of Transportation posts the latest fatality messages on signs along select traffic corridors as part of a safety campaign. Their logic is simple: Tell people to drive with care by reminding them of the dangers on the road.
But when the researchers looked at the data, they found that the number of crashes increased by 1.52 percent within three miles of these signs when compared with the same locations during the same month in previous years when signs did not show fatality information. That impact is similar to raising the speed limit by four miles or decreasing the number of highway troopers by 10 percent.
The scientists calculated that these messages contributed to 2,600 additional crashes and 16 deaths annually. They also found a social cost, meaning the financial expense borne by society as a whole due to these crashes, of $377 million per year, in Texas alone.
The cause, they argue, is distracted driving. Much like incoming texts or phone calls, these “in-your-face” messages grab your attention and undermine your focus on the road. The signs are particularly distracting and dangerous because, in communicating that many people died doing exactly what you are doing, they cause anxiety. Supporting this hypothesis, the scientists discovered that crashes increase when the signs report higher numbers of deaths. Thus, later in the year, as that total mortality figure goes up, so do the percentage of crashes.
Boomerang effects happen when those with authority, in government or business, fail to pay attention to the science. These leaders rely on armchair psychology and gut intuitions on what should work, rather than measuring what does work.
That change over time is not simply a function of changing weather, the study’s authors observed. They also found that the increase in car crashes is greatest in more complex road segments, which require greater focus to navigate.
The overall findings represent what behavioral scientists like myself call a “boomerang effect,” meaning an intervention that produces consequences opposite to those intended. Unfortunately, these effects are all too common. Between 1998 and 2004, Congress funded the $1 billion National Youth Anti-Drug Media Campaign, which famously boomeranged. Using professional advertising and public relations firms, the campaign bombarded kids aged 9 to 18 with anti-drug messaging, focused on marijuana, on TV, radio, magazines, and websites. A 2008 study funded by the National Institutes of Health found that children and teens saw these ads two to three times per week. However, more exposure to this advertising increased the likelihood that youth used marijuana. Why? Surveys and interviews suggested that young people who saw the ads got the impression that many of their peers used marijuana. As a result, they became more likely to use the drug themselves.
Boomerang effects happen when those with authority, in government or business, fail to pay attention to the science. These leaders rely on armchair psychology and gut intuitions on what should work, rather than measuring what does work.
To be clear, message campaigns—whether on electronic signs or through advertisements—can have a substantial effect on behavior. Extensive research reveals that people can be influenced by “nudges,” which shape the environment to influence their behavior in a predictable manner. For example, a successful campaign to reduce car accidents involved sending smartphone notifications that helped drivers evaluate their performance after each trip. These messages informed drivers of their personal average and best performance, as measured by accelerometers and gyroscopes. The campaign, which ran over 21 months, significantly reduced accident frequency.
Nudges work best when rigorously tested with small-scale experiments that evaluate their impact. Because behavioral scientists are infrequently consulted in creating these policies, some studies suggest that only 62 percent have a statistically significant effect. Other research reveals that up to 15 percent of desired interventions may backfire.
In the case of roadside mortality signage, the data are damning. The new research based on the Texas signs aligns with several past studies. For instance, research has shown that increasing people’s anxiety causes them to drive worse. Another, a Virginia Tech study in a laboratory setting, found that showing drivers fatality messages increased what psychologists call “cognitive load,” or the amount of information your brain is processing, with emotionally-salient information being especially burdensome and preoccupying, thus causing more distraction.
Nonetheless, Texas, along with at least 28 other states, has pursued mortality messaging campaigns since 2012, without testing them effectively. Behavioral science is critical here: when road signs are tested by people without expertise in how minds work, the results are often counterproductive. For example, the Virginia Tech research looked at road signs that used humor, popular culture, sports, and other nontraditional themes with the goal of provoking an emotional response. When they measured how participants responded to these signs, they noticed greater cognitive activation and attention in the brain. Thus, the researchers decided, the signs worked. But a behavioral scientist would note that increased attention likely contributes to the signs’ failure. As the just-published study in Science makes clear, distracting, emotionally-loaded signs are dangerous to drivers.
But there is good news. First, in most cases, it’s very doable to run an effective small-scale study testing an intervention. States could set up a safety campaign with a few electric signs in a diversity of settings and evaluate the impact over three months on driver crashes after seeing the signs. Policymakers could ask researchers to track the data as they run ads for a few months in a variety of nationally representative markets for a few months and assess their effectiveness. They could also ask behavioral scientists whether their proposals are well designed, whether similar policies have been tried previously in other places, and how these policies have worked in practice.
Everyday citizens can write to and call their elected officials to ask them to make this kind of research a priority before embracing an untested safety campaign. More broadly, you can encourage them to avoid relying on armchair psychology and to test their intuitions before deploying initiatives that might place the public under threat.
I walked through the Dong Makkhai forest-products market, just outside of Vientiane, the laid-back capital of the Lao Peoples Democratic Republic or Lao PDR. Piled on rough display tables were varieties of six-legged wildlife–grasshoppers, small white crickets, house crickets, mole crickets, wasps, wasp eggs and larvae, dragonflies, and dung beetles. Some were roasted or fried, but in a few cases, still alive and scrabbling at the bottom of deep plastic bowls. I crunched on some fried crickets and larvae.
One stall offered Giant Asian hornets, both babies and adults. I suppressed my inner squirm and, in the interests of world food security and equity, accepted an offer of the soft, velvety larva; they were smooth on the tongue and of a pleasantly cool, buttery-custard consistency. Because the seller had already given me a free sample, I felt obliged to buy a chunk of the nest with larvae and some dead adults, which the seller mixed with kaffir lime leaves.
The year was 2016 and I was in Lao PDR because Veterinarians without Borders/Vétérinaires sans Frontières-Canada had initiated a project on small-scale cricket farming. The intent was to organize and encourage rural women to grow crickets as a source of supplementary protein and sell them at the market for cash. As a veterinary epidemiologist, I had been trained to exterminate disease spreading insects—Lyme disease-carrying ticks, kissing bugs that carry American Sleeping Sickness and mosquitoes carrying malaria, West Nile and Zika. Now, as part of a global wave promoting insects as a sustainable food source, I was being asked to view arthropods as micro-livestock, and devise management methods to keep them alive and healthy. It was a bit of a mind-bender.
The 21st century wave of entomophagy, or insect eating, first surged in the early 2010s, promoted by a research centre in Wageningen, a university in the Netherlands, conferences organized by the Food and Agriculture Organization of the United Nations, and enthusiastic endorsements by culinary adventurers and celebrities from Europeanized cultures. Headlines announced that two billion people around the world already ate insects, and that if everyone adopted entomophagy we could reduce greenhouse gases, mitigate climate change, and reign in profligate land and water use associated with industrial livestock production.
Furthermore, eating insects was better for human health than eating beef. If we were going to feed the estimated nine billion people with whom we will share the earth in 2050, we would need to make some radical changes in our agriculture and food systems. As one author proclaimed, entomophagy presented us with a last great chance to save the planet.
In 2010, in Kunming, a friend had served me deep-fried bamboo worms. I ate them to be polite. They tasted like French fries, but with heads.
The more recent data suggests that the number of people who eat insects in various forms, though sizeable, may be closer to several hundreds of millions. I knew that from several decades of international veterinary work. Sometimes, for me, insect eating has been simply a way of acknowledging cultural diversity. In 2010, in Kunming, a friend had served me deep-fried bamboo worms. I ate them to be polite. They tasted like French fries, but with heads. My friend said he preferred them chewier. I never thought about them much after that. I certainly had not thought about them as ingredients for human health.
Is consuming insects good for human health? Researchers over the past decade have begun to tease that apart. Some think it might not be useful to use the all-encompassing term insect at all; we don’t lump cows, pigs, chickens into one culinary category. Which insects are we talking about? What are they fed? Were they farmed or foraged? Which stages of the insects are we eating? Do we eat them directly or roasted and ground up?
The overall research indicates that, in general, the usual farmed insects (crickets, locusts, mealworms, soldier fly larvae) have high levels of protein and other important nutrients. If insects are foraged by small groups in Laos, they provide excellent food supplements. Large scale foraging in response to global markets can be incredibly destructive, but soldier fly larvae fed on food waste and used as a substitute for ground up anchovies for farmed fish (as Enterra Feed in Canada does) improves ecological sustainability.
Entomophagy alone might not save the planet, but it does give us an unprecedented opportunity to rethink how we produce and harvest protein.
The author enjoys insects from the Dong Makkhai forest-products market, just outside of Vientiane, the capital of the Lao Peoples Democratic Republic.
Between 1961 and 2018, world chicken production increased from 4 billion to 20 billion, pork from 200 million to over 100 billion pigs, human populations doubled from 3.5 billion to more than 7 billion, and life expectancy (on average) from 52 to 72 years. These dramatic increases in food production are the result of narrowly focused scientific studies, identifying specific nutrients, antibiotics, vaccines and genetics. What has been missing is any sort of peripheral vision: what are the unintended consequences of our narrowly defined success?
If we look more broadly, we can see that this narrowly defined success led to industrial farming, which caused wealth, health and labor inequities; polluted the environment; and created grounds for disease outbreaks. Recent generations of Europeanized people inherited the ideas of eating cows, pigs and chickens, along with their products, so we were focused only on growing them as efficiently as possible. With insects, we have an exciting chance to start from scratch. Because, for Europeanized people, insect eating is so strange, we are given the chance to reimagine our whole food system in consultation with local experts in Asia and Africa (many of them villagers), and to bring together the best of both locally adapted food production and global distribution.
For this to happen, we will need to change the dietary habits of the big meat eaters. How can we get accustomed to eating bugs? There’s no one answer, but there are a few ways. In many cases, insects are ground up and added as protein supplements to foods like crackers or bars. In certain restaurants, the chefs want you to get used to seeing the bugs as you eat them. At Le Feston Nu in Paris, the Arlo Guthrie look-alike bartender poured me a beer and brought out five small plates, each featuring a different insect in a nest of figs, sun-dried tomatoes, raisins, and chopped dried tropical fruits: buffalo worms, crickets, large grasshoppers (all just crunchy and no strong flavour, maybe a little nutty), small black ants (sour bite), and fat grubs with a beak, which I later identified as palm weevil larvae, tasting a bit like dried figs.
Some entomophagy advertising has used esthetically pleasing presentations in classy restaurants. In London, at the Archipelago restaurant, I dined on Summer Nights (pan fried chermoula crickets, quinoa, spinach and dried fruit), Love-Bug Salad (baby greens with an accompanying dish of zingy, crunchy mealworms fried in olive oil, chilis, lemon grass, and garlic), Bushman’s Cavi-Err (caramel mealworms, bilinis, coconut cream and vodka jelly), and Medieaval Hive (brown butter ice cream, honey and butter caramel sauce and a baby bee drone).
The Archipelago restaurant in London serves up a Love-Bug Salad: baby greens with an accompanying dish of zingy, crunchy mealworms fried in olive oil, chilis, lemon grass, and garlic.
Some chefs, like Tokyo-based Shoichi Uchiyama, try to entice people with sidewalk cooking lessons. Uchiyama's menu included hornet larvae, silkworm pupae, and silkworms. The silkworm pupae were white and pink and yellow. We snipped off the ends and the larvae dropped out. My friend Zen Kawabata roasted them in a small pan over a camp stove in the street to get the "chaff" off. We made tea from the feces of worms that had fed on cherry blossoms—the tea smelled of the blossoms. One of Uchiyama-san’s assistants made noodles from buckwheat dough that included powdered whole bees.
At a book reading in a Tokyo bookstore, someone handed me a copy of the Japanese celebrity scandal magazine Friday, opened to an article celebrating the “charms of insect eating.” In a photo, scantily-clad girls were drinking vodka and nibbling giant water bugs dubbed as toe-biters, along with pickled and fried locusts and butterfly larvae. If celebrities embraced bug-eating, others might follow. When asked to prepare an article on entomophagy for the high fashion Sorbet Magazine, I started by describing a clip of Nicole Kidman delicately snacking on insects.
Taking a page from the success story of MacDonald’s, we might consider targeting children and school lunches. Kids don’t lug around the same dietary baggage as the grownups, and they can carry forward new eating habits for the long term. When I offered roasted crickets to my grandchildren, they scarfed them down. I asked my five-year-old granddaughter what she thought: she preferred the mealworms to the crickets – they didn’t have legs that caught in her teeth.
Entomo Farms in Ontario, the province where I live, was described in 2015 by Canadian Business magazine as North America’s largest supplier of edible insects for human consumption. When visiting, I popped some of their roasted crickets into my mouth. They were crunchy, a little nutty. Nothing to get squeamish over. Perhaps the human consumption is indeed growing—my wife, at least, has joined me in my entomophagy adventures. When we celebrated our wedding anniversary at the Public Bar and Restaurant in Brisbane, Australia, the “Kang Kong Worms” and “Salmon, Manuka Honey, and Black Ants” seemed almost normal. Of course, the champagne helped.