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."
On today’s episode of Making Sense of Science, I’m honored to be joined by Dr. Paul Song, a physician, oncologist, progressive activist and biotech chief medical officer. Through his company, NKGen Biotech, Dr. Song is leveraging the power of patients’ own immune systems by supercharging the body’s natural killer cells to make new treatments for Alzheimer’s and cancer.
Whereas other treatments for Alzheimer’s focus directly on reducing the build-up of proteins in the brain such as amyloid and tau in patients will mild cognitive impairment, NKGen is seeking to help patients that much of the rest of the medical community has written off as hopeless cases, those with late stage Alzheimer’s. And in small studies, NKGen has shown remarkable results, even improvement in the symptoms of people with these very progressed forms of Alzheimer’s, above and beyond slowing down the disease.
In the realm of cancer, Dr. Song is similarly setting his sights on another group of patients for whom treatment options are few and far between: people with solid tumors. Whereas some gradual progress has been made in treating blood cancers such as certain leukemias in past few decades, solid tumors have been even more of a challenge. But Dr. Song’s approach of using natural killer cells to treat solid tumors is promising. You may have heard of CAR-T, which uses genetic engineering to introduce cells into the body that have a particular function to help treat a disease. NKGen focuses on other means to enhance the 40 plus receptors of natural killer cells, making them more receptive and sensitive to picking out cancer cells.
Paul Y. Song, MD is currently CEO and Vice Chairman of NKGen Biotech. Dr. Song’s last clinical role was Asst. Professor at the Samuel Oschin Cancer Center at Cedars Sinai Medical Center.
Dr. Song served as the very first visiting fellow on healthcare policy in the California Department of Insurance in 2013. He is currently on the advisory board of the Pritzker School of Molecular Engineering at the University of Chicago and a board member of Mercy Corps, The Center for Health and Democracy, and Gideon’s Promise.
Dr. Song graduated with honors from the University of Chicago and received his MD from George Washington University. He completed his residency in radiation oncology at the University of Chicago where he served as Chief Resident and did a brachytherapy fellowship at the Institute Gustave Roussy in Villejuif, France. He was also awarded an ASTRO research fellowship in 1995 for his research in radiation inducible gene therapy.
With Dr. Song’s leadership, NKGen Biotech’s work on natural killer cells represents cutting-edge science leading to key findings and important pieces of the puzzle for treating two of humanity’s most intractable diseases.
Show links
- Paul Song LinkedIn
- NKGen Biotech on Twitter - @NKGenBiotech
- NKGen Website: https://nkgenbiotech.com/
- NKGen appoints Paul Song
- Patient Story: https://pix11.com/news/local-news/long-island/promising-new-treatment-for-advanced-alzheimers-patients/
- FDA Clearance: https://nkgenbiotech.com/nkgen-biotech-receives-ind-clearance-from-fda-for-snk02-allogeneic-natural-killer-cell-therapy-for-solid-tumors/Q3 earnings data: https://www.nasdaq.com/press-release/nkgen-biotech-inc.-reports-third-quarter-2023-financial-results-and-business
Is there a robot nanny in your child's future?
From ROBOTS AND THE PEOPLE WHO LOVE THEM: Holding on to Our Humanity in an Age of Social Robots by Eve Herold. Copyright © 2024 by the author and reprinted by permission of St. Martin’s Publishing Group.
Could the use of robots take some of the workload off teachers, add engagement among students, and ultimately invigorate learning by taking it to a new level that is more consonant with the everyday experiences of young people? Do robots have the potential to become full-fledged educators and further push human teachers out of the profession? The preponderance of opinion on this subject is that, just as AI and medical technology are not going to eliminate doctors, robot teachers will never replace human teachers. Rather, they will change the job of teaching.
A 2017 study led by Google executive James Manyika suggested that skills like creativity, emotional intelligence, and communication will always be needed in the classroom and that robots aren’t likely to provide them at the same level that humans naturally do. But robot teachers do bring advantages, such as a depth of subject knowledge that teachers can’t match, and they’re great for student engagement.
The teacher and robot can complement each other in new ways, with the teacher facilitating interactions between robots and students. So far, this is the case with teaching “assistants” being adopted now in China, Japan, the U.S., and Europe. In this scenario, the robot (usually the SoftBank child-size robot NAO) is a tool for teaching mainly science, technology, engineering, and math (the STEM subjects), but the teacher is very involved in planning, overseeing, and evaluating progress. The students get an entertaining and enriched learning experience, and some of the teaching load is taken off the teacher. At least, that’s what researchers have been able to observe so far.
To be sure, there are some powerful arguments for having robots in the classroom. A not-to-be-underestimated one is that robots “speak the language” of today’s children, who have been steeped in technology since birth. These children are adept at navigating a media-rich environment that is highly visual and interactive. They are plugged into the Internet 24-7. They consume music, games, and huge numbers of videos on a weekly basis. They expect to be dazzled because they are used to being dazzled by more and more spectacular displays of digital artistry. Education has to compete with social media and the entertainment vehicles of students’ everyday lives.
Another compelling argument for teaching robots is that they help prepare students for the technological realities they will encounter in the real world when robots will be ubiquitous. From childhood on, they will be interacting and collaborating with robots in every sphere of their lives from the jobs they do to dealing with retail robots and helper robots in the home. Including robots in the classroom is one way of making sure that children of all socioeconomic backgrounds will be better prepared for a highly automated age, when successfully using robots will be as essential as reading and writing. We’ve already crossed this threshold with computers and smartphones.
Students need multimedia entertainment with their teaching. This is something robots can provide through their ability to connect to the Internet and act as a centralized host to videos, music, and games. Children also need interaction, something robots can deliver up to a point, but which humans can surpass. The education of a child is not just intended to make them technologically functional in a wired world, it’s to help them grow in intellectual, creative, social, and emotional ways. When considered through this perspective, it opens the door to questions concerning just how far robots should go. Robots don’t just teach and engage children; they’re designed to tug at their heartstrings.
It’s no coincidence that many toy makers and manufacturers are designing cute robots that look and behave like real children or animals, says Turkle. “When they make eye contact and gesture toward us, they predispose us to view them as thinking and caring,” she has written in The Washington Post. “They are designed to be cute, to provide a nurturing response” from the child. As mentioned previously, this nurturing experience is a powerful vehicle for drawing children in and promoting strong attachment. But should children really love their robots?
ROBOTS AND THE PEOPLE WHO LOVE THEM: Holding on to Our Humanity in an Age of Social Robots by Eve Herold (January 9, 2024).
St. Martin’s Publishing Group
The problem, once again, is that a child can be lulled into thinking that she’s in an actual relationship, when a robot can’t possibly love her back. If adults have these vulnerabilities, what might such asymmetrical relationships do to the emotional development of a small child? Turkle notes that while we tend to ascribe a mind and emotions to a socially interactive robot, “simulated thinking may be thinking, but simulated feeling is never feeling, and simulated love is never love.”
Always a consideration is the fact that in the first few years of life, a child’s brain is undergoing rapid growth and development that will form the foundation of their lifelong emotional health. These formative experiences are literally shaping the child’s brain, their expectations, and their view of the world and their place in it. In Alone Together, Turkle asks: What are we saying to children about their importance to us when we’re willing to outsource their care to a robot? A child might be superficially entertained by the robot while his self-esteem is systematically undermined.
Research has emerged showing that there are clear downsides to child-robot relationships.
Still, in the case of robot nannies in the home, is active, playful engagement with a robot for a few hours a day any more harmful than several hours in front of a TV or with an iPad? Some, like Xiong, regard interacting with a robot as better than mere passive entertainment. iPal’s manufacturers say that their robot can’t replace parents or teachers and is best used by three- to eight-year-olds after school, while they wait for their parents to get off work. But as robots become ever-more sophisticated, they’re expected to perform more of the tasks of day-to-day care and to be much more emotionally advanced. There is no question children will form deep attachments to some of them. And research has emerged showing that there are clear downsides to child-robot relationships.
Some studies, performed by Turkle and fellow MIT colleague Cynthia Breazeal, have revealed a darker side to the child-robot bond. Turkle has reported extensively on these studies in The Washington Post and in her book Alone Together. Most children love robots, but some act out their inner bully on the hapless machines, hitting and kicking them and otherwise trying to hurt them. The trouble is that the robot can’t fight back, teaching children that they can bully and abuse without consequences. As in any other robot relationship, such harmful behavior could carry over into the child’s human relationships.
And, ironically, it turns out that communicative machines don’t actually teach kids good communication skills. It’s well known that parent-child communication in the first three years of life sets the stage for a very young child’s intellectual and academic success. Verbal back-and-forth with parents and care-givers is like fuel for a child’s growing brain. One article that examined several types of play and their effect on children’s communication skills, published in JAMA Pediatrics in 2015, showed that babies who played with electronic toys—like the popular robot dog Aibo—show a decrease in both the quantity and quality of their language skills.
Anna V. Sosa of the Child Speech and Language Lab at Northern Arizona University studied twenty-six ten- to sixteen- month-old infants to compare the growth of their language skills after they played with three types of toys: electronic toys like a baby laptop and talking farm; traditional toys like wooden puzzles and building blocks; and books read aloud by their parents. The play that produced the most growth in verbal ability was having books read to them by a caregiver, followed by play with traditional toys. Language gains after playing with electronic toys came dead last. This form of play involved the least use of adult words, the least conversational turntaking, and the least verbalizations from the children. While the study sample was small, it’s not hard to extrapolate that no electronic toy or even more abled robot could supply the intimate responsiveness of a parent reading stories to a child, explaining new words, answering the child’s questions, and modeling the kind of back- and-forth interaction that promotes empathy and reciprocity in relationships.
***
Most experts acknowledge that robots can be valuable educational tools. But they can’t make a child feel truly loved, validated, and valued. That’s the job of parents, and when parents abdicate this responsibility, it’s not only the child who misses out on one of life’s most profound experiences.
We really don’t know how the tech-savvy children of today will ultimately process their attachments to robots and whether they will be excessively predisposed to choosing robot companionship over that of humans. It’s possible their techno literacy will draw for them a bold line between real life and a quasi-imaginary history with a robot. But it will be decades before we see long-term studies culminating in sufficient data to help scientists, and the rest of us, to parse out the effects of a lifetime spent with robots.
This is an excerpt from ROBOTS AND THE PEOPLE WHO LOVE THEM: Holding on to Our Humanity in an Age of Social Robots by Eve Herold. The book will be published on January 9, 2024.