Your Digital Avatar May One Day Get Sick Before You Do
Artificial intelligence is everywhere, just not in the way you think it is.
These networks, loosely designed after the human brain, are interconnected computers that have the ability to "learn."
"There's the perception of AI in the glossy magazines," says Anders Kofod-Petersen, a professor of Artificial Intelligence at the Norwegian University of Science and Technology. "That's the sci-fi version. It resembles the small guy in the movie AI. It might be benevolent or it might be evil, but it's generally intelligent and conscious."
"And this is, of course, as far from the truth as you can possibly get."
What Exactly Is Artificial Intelligence, Anyway?
Let's start with how you got to this piece. You likely came to it through social media. Your Facebook account, Twitter feed, or perhaps a Google search. AI influences all of those things, machine learning helping to run the algorithms that decide what you see, when, and where. AI isn't the little humanoid figure; it's the system that controls the figure.
"AI is being confused with robotics," Eleonore Pauwels, Director of the Anticipatory Intelligence Lab with the Science and Technology Innovation Program at the Wilson Center, says. "What AI is right now is a data optimization system, a very powerful data optimization system."
The revolution in recent years hasn't come from the method scientists and other researchers use. The general ideas and philosophies have been around since the late 1960s. Instead, the big change has been the dramatic increase in computing power, primarily due to the development of neural networks. These networks, loosely designed after the human brain, are interconnected computers that have the ability to "learn." An AI, for example, can be taught to spot a picture of a cat by looking at hundreds of thousands of pictures that have been labeled "cat" and "learning" what a cat looks like. Or an AI can beat a human at Go, an achievement that just five years ago Kofod-Petersen thought wouldn't be accomplished for decades.
"It's very difficult to argue that something is intelligent if it can't learn, and these algorithms are getting pretty good at learning stuff. What they are not good at is learning how to learn."
Medicine is the field where this expertise in perception tasks might have the most influence. It's already having an impact as iPhones use AI to detect cancer, Apple watches alert the wearer to a heart problem, AI spots tuberculosis and the spread of breast cancer with a higher accuracy than human doctors, and more. Every few months, another study demonstrates more possibility. (The New Yorker published an article about medicine and AI last year, so you know it's a serious topic.)
But this is only the beginning. "I personally think genomics and precision medicine is where AI is going to be the biggest game-changer," Pauwels says. "It's going to completely change how we think about health, our genomes, and how we think about our relationship between our genotype and phenotype."
The Fundamental Breakthrough That Must Be Solved
To get there, however, researchers will need to make another breakthrough, and there's debate about how long that will take. Kofod-Petersen explains: "If we want to move from this narrow intelligence to this broader intelligence, that's a very difficult problem. It basically boils down to that we haven't got a clue about what intelligence actually is. We don't know what intelligence means in a biological sense. We think we might recognize it but we're not completely sure. There isn't a working definition. We kind of agree with the biologists that learning is an aspect of it. It's very difficult to argue that something is intelligent if it can't learn, and these algorithms are getting pretty good at learning stuff. What they are not good at is learning how to learn. They can learn specific tasks but we haven't approached how to teach them to learn to learn."
In other words, current AI is very, very good at identifying that a picture of a cat is, in fact, a cat – and getting better at doing so at an incredibly rapid pace – but the system only knows what a "cat" is because that's what a programmer told it a furry thing with whiskers and two pointy ears is called. If the programmer instead decided to label the training images as "dogs," the AI wouldn't say "no, that's a cat." Instead, it would simply call a furry thing with whiskers and two pointy ears a dog. AI systems lack the explicit inference that humans do effortlessly, almost without thinking.
Pauwels believes that the next step is for AI to transition from supervised to unsupervised learning. The latter means that the AI isn't answering questions that a programmer asks it ("Is this a cat?"). Instead, it's almost like it's looking at the data it has, coming up with its own questions and hypothesis, and answering them or putting them to the test. Combining this ability with the frankly insane processing power of the computer system could result in game-changing discoveries.
In the not-too-distant future, a doctor could run diagnostics on a digital avatar, watching which medical conditions present themselves before the person gets sick in real life.
One company in China plans to develop a way to create a digital avatar of an individual person, then simulate that person's health and medical information into the future. In the not-too-distant future, a doctor could run diagnostics on a digital avatar, watching which medical conditions presented themselves – cancer or a heart condition or anything, really – and help the real-life version prevent those conditions from beginning or treating them before they became a life-threatening issue.
That, obviously, would be an incredibly powerful technology, and it's just one of the many possibilities that unsupervised AI presents. It's also terrifying in the potential for misuse. Even the term "unsupervised AI" brings to mind a dystopian landscape where AI takes over and enslaves humanity. (Pick your favorite movie. There are dozens.) This is a concern, something for developers, programmers, and scientists to consider as they build the systems of the future.
The Ethical Problem That Deserves More Attention
But the more immediate concern about AI is much more mundane. We think of AI as an unbiased system. That's incorrect. Algorithms, after all, are designed by someone or a team, and those people have explicit or implicit biases. Intentionally, or more likely not, they introduce these biases into the very code that forms the basis for the AI. Current systems have a bias against people of color. Facebook tried to rectify the situation and failed. These are two small examples of a larger, potentially systemic problem.
It's vital and necessary for the people developing AI today to be aware of these issues. And, yes, avoid sending us to the brink of a James Cameron movie. But AI is too powerful a tool to ignore. Today, it's identifying cats and on the verge of detecting cancer. In not too many tomorrows, it will be on the forefront of medical innovation. If we are careful, aware, and smart, it will help simulate results, create designer drugs, and revolutionize individualize medicine. "AI is the only way to get there," Pauwels says.
If you look back on the last century of scientific achievements, you might notice that most of the scientists we celebrate are overwhelmingly white, while scientists of color take a backseat. Since the Nobel Prize was introduced in 1901, for example, no black scientists have landed this prestigious award.
The work of black women scientists has gone unrecognized in particular. Their work uncredited and often stolen, black women have nevertheless contributed to some of the most important advancements of the last 100 years, from the polio vaccine to GPS.
Here are five black women who have changed science forever.
Dr. May Edward Chinn
Dr. May Edward Chinn practicing medicine in Harlem
George B. Davis, PhD.
Chinn was born to poor parents in New York City just before the start of the 20th century. Although she showed great promise as a pianist, playing with the legendary musician Paul Robeson throughout the 1920s, she decided to study medicine instead. Chinn, like other black doctors of the time, were barred from studying or practicing in New York hospitals. So Chinn formed a private practice and made house calls, sometimes operating in patients’ living rooms, using an ironing board as a makeshift operating table.
Chinn worked among the city’s poor, and in doing this, started to notice her patients had late-stage cancers that often had gone undetected or untreated for years. To learn more about cancer and its prevention, Chinn begged information off white doctors who were willing to share with her, and even accompanied her patients to other clinic appointments in the city, claiming to be the family physician. Chinn took this information and integrated it into her own practice, creating guidelines for early cancer detection that were revolutionary at the time—for instance, checking patient health histories, checking family histories, performing routine pap smears, and screening patients for cancer even before they showed symptoms. For years, Chinn was the only black female doctor working in Harlem, and she continued to work closely with the poor and advocate for early cancer screenings until she retired at age 81.
Alice Ball
Pictorial Press Ltd/Alamy
Alice Ball was a chemist best known for her groundbreaking work on the development of the “Ball Method,” the first successful treatment for those suffering from leprosy during the early 20th century.
In 1916, while she was an undergraduate student at the University of Hawaii, Ball studied the effects of Chaulmoogra oil in treating leprosy. This oil was a well-established therapy in Asian countries, but it had such a foul taste and led to such unpleasant side effects that many patients refused to take it.
So Ball developed a method to isolate and extract the active compounds from Chaulmoogra oil to create an injectable medicine. This marked a significant breakthrough in leprosy treatment and became the standard of care for several decades afterward.
Unfortunately, Ball died before she could publish her results, and credit for this discovery was given to another scientist. One of her colleagues, however, was able to properly credit her in a publication in 1922.
Henrietta Lacks
onathan Newton/The Washington Post/Getty
The person who arguably contributed the most to scientific research in the last century, surprisingly, wasn’t even a scientist. Henrietta Lacks was a tobacco farmer and mother of five children who lived in Maryland during the 1940s. In 1951, Lacks visited Johns Hopkins Hospital where doctors found a cancerous tumor on her cervix. Before treating the tumor, the doctor who examined Lacks clipped two small samples of tissue from Lacks’ cervix without her knowledge or consent—something unthinkable today thanks to informed consent practices, but commonplace back then.
As Lacks underwent treatment for her cancer, her tissue samples made their way to the desk of George Otto Gey, a cancer researcher at Johns Hopkins. He noticed that unlike the other cell cultures that came into his lab, Lacks’ cells grew and multiplied instead of dying out. Lacks’ cells were “immortal,” meaning that because of a genetic defect, they were able to reproduce indefinitely as long as certain conditions were kept stable inside the lab.
Gey started shipping Lacks’ cells to other researchers across the globe, and scientists were thrilled to have an unlimited amount of sturdy human cells with which to experiment. Long after Lacks died of cervical cancer in 1951, her cells continued to multiply and scientists continued to use them to develop cancer treatments, to learn more about HIV/AIDS, to pioneer fertility treatments like in vitro fertilization, and to develop the polio vaccine. To this day, Lacks’ cells have saved an estimated 10 million lives, and her family is beginning to get the compensation and recognition that Henrietta deserved.
Dr. Gladys West
Andre West
Gladys West was a mathematician who helped invent something nearly everyone uses today. West started her career in the 1950s at the Naval Surface Warfare Center Dahlgren Division in Virginia, and took data from satellites to create a mathematical model of the Earth’s shape and gravitational field. This important work would lay the groundwork for the technology that would later become the Global Positioning System, or GPS. West’s work was not widely recognized until she was honored by the US Air Force in 2018.
Dr. Kizzmekia "Kizzy" Corbett
TIME Magazine
At just 35 years old, immunologist Kizzmekia “Kizzy” Corbett has already made history. A viral immunologist by training, Corbett studied coronaviruses at the National Institutes of Health (NIH) and researched possible vaccines for coronaviruses such as SARS (Severe Acute Respiratory Syndrome) and MERS (Middle East Respiratory Syndrome).
At the start of the COVID pandemic, Corbett and her team at the NIH partnered with pharmaceutical giant Moderna to develop an mRNA-based vaccine against the virus. Corbett’s previous work with mRNA and coronaviruses was vital in developing the vaccine, which became one of the first to be authorized for emergency use in the United States. The vaccine, along with others, is responsible for saving an estimated 14 million lives.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