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.
Gene Transfer Leads to Longer Life and Healthspan
The naked mole rat won’t win any beauty contests, but it could possibly win in the talent category. Its superpower: fighting the aging process to live several times longer than other animals its size, in a state of youthful vigor.
It’s believed that naked mole rats experience all the normal processes of wear and tear over their lifespan, but that they’re exceptionally good at repairing the damage from oxygen free radicals and the DNA errors that accumulate over time. Even though they possess genes that make them vulnerable to cancer, they rarely develop the disease, or any other age-related disease, for that matter. Naked mole rats are known to live for over 40 years without any signs of aging, whereas mice live on average about two years and are highly prone to cancer.
Now, these remarkable animals may be able to share their superpower with other species. In August, a study provided what may be the first proof-of-principle that genetic material transferred from one species can increase both longevity and healthspan in a recipient animal.
There are several theories to explain the naked mole rat’s longevity, but the one explored in the study, published in Nature, is based on the abundance of large-molecule high-molecular mass hyaluronic acid (HMM-HA).
A small molecule version of hyaluronic acid is commonly added to skin moisturizers and cosmetics that are marketed as ways to keep skin youthful, but this version, just applied to the skin, won’t have a dramatic anti-aging effect. The naked mole rat has an abundance of the much-larger molecule, HMM-HA, in the chemical-rich solution between cells throughout its body. But does the HMM-HA actually govern the extraordinary longevity and healthspan of the naked mole rat?
To answer this question, Dr. Vera Gorbunova, a professor of biology and oncology at the University of Rochester, and her team created a mouse model containing the naked mole rat gene hyaluronic acid synthase 2, or nmrHas2. It turned out that the mice receiving this gene during their early developmental stage also expressed HMM-HA.
The researchers found that the effects of the HMM-HA molecule in the mice were marked and diverse, exceeding the expectations of the study’s co-authors. High-molecular mass hyaluronic acid was more abundant in kidneys, muscles and other organs of the Has2 mice compared to control mice.
In addition, the altered mice had a much lower incidence of cancer. Seventy percent of the control mice eventually developed cancer, compared to only 57 percent of the altered mice, even after several techniques were used to induce the disease. The biggest difference occurred in the oldest mice, where the cancer incidence for the Has2 mice and the controls was 47 percent and 83 percent, respectively.
With regard to longevity, Has2 males increased their lifespan by more than 16 percent and the females added 9 percent. “Somehow the effect is much more pronounced in male mice, and we don’t have a perfect answer as to why,” says Dr. Gorbunova. Another improvement was in the healthspan of the altered mice: the number of years they spent in a state of relative youth. There’s a frailty index for mice, which includes body weight, mobility, grip strength, vision and hearing, in addition to overall conditions such as the health of the coat and body temperature. The Has2 mice scored lower in frailty than the controls by all measures. They also performed better in tests of locomotion and coordination, and in bone density.
Gorbunova’s results show that a gene artificially transferred from one species can have a beneficial effect on another species for longevity, something that had never been demonstrated before. This finding is “quite spectacular,” said Steven Austad, a biologist at the University of Alabama at Birmingham, who was not involved in the study.
Just as in lifespan, the effects in various organs and systems varied between the sexes, a common occurrence in longevity research, according to Austad, who authored the book Methuselah’s Zoo and specializes in the biological differences between species. “We have ten drugs that we can give to mice to make them live longer,” he says, “and all of them work better in one sex than in the other.” This suggests that more attention needs to be paid to the different effects of anti-aging strategies between the sexes, as well as gender differences in healthspan.
According to the study authors, the HMM-HA molecule delivered these benefits by reducing inflammation and senescence (cell dysfunction and death). The molecule also caused a variety of other benefits, including an upregulation of genes involved in the function of mitochondria, the powerhouses of the cells. These mechanisms are implicated in the aging process, and in human disease. In humans, virtually all noncommunicable diseases entail an acceleration of the aging process.
So, would the gene that creates HMM-HA have similar benefits for longevity in humans? “We think about these questions a lot,” Gorbunova says. “It’s been done by injections in certain patients, but it has a local effect in the treatment of organs affected by disease,” which could offer some benefits, she added.
“Mice are very short-lived and cancer-prone, and the effects are small,” says Steven Austad, a biologist at the University of Alabama at Birmingham. “But they did live longer and stay healthy longer, which is remarkable.”
As for a gene therapy to introduce the nmrHas2 gene into humans to obtain a global result, she’s skeptical because of the complexity involved. Gorbunova notes that there are potential dangers in introducing an animal gene into humans, such as immune responses or allergic reactions.
Austad is equally cautious about a gene therapy. “What this study says is that you can take something a species does well and transfer at least some of that into a new species. It opens up the way, but you may need to transfer six or eight or ten genes into a human” to get the large effect desired. Humans are much more complex and contain many more genes than mice, and all systems in a biological organism are intricately connected. One naked mole rat gene may not make a big difference when it interacts with human genes, metabolism and physiology.
Still, Austad thinks the possibilities are tantalizing. “Mice are very short-lived and cancer-prone, and the effects are small,” he says. “But they did live longer and stay healthy longer, which is remarkable.”
As for further research, says Austad, “The first place to look is the skin” to see if the nmrHas2 gene and the HMM-HA it produces can reduce the chance of cancer. Austad added that it would be straightforward to use the gene to try to prevent cancer in skin cells in a dish to see if it prevents cancer. It would not be hard to do. “We don’t know of any downsides to hyaluronic acid in skin, because it’s already used in skin products, and you could look at this fairly quickly.”
“Aging mechanisms evolved over a long time,” says Gorbunova, “so in aging there are multiple mechanisms working together that affect each other.” All of these processes could play a part and almost certainly differ from one species to the next.
“HMM-HA molecules are large, but we’re now looking for a small-molecule drug that would slow it’s breakdown,” she says. “And we’re looking for inhibitors, now being tested in mice, that would hinder the breakdown of hyaluronic acid.” Gorbunova has found a natural, plant-based product that acts as an inhibitor and could potentially be taken as a supplement. Ultimately, though, she thinks that drug development will be the safest and most effective approach to delivering HMM-HA for anti-aging.
In recent years, researchers of Alzheimer’s have made progress in figuring out the complex factors that lead to the disease. Yet, the root cause, or causes, of Alzheimer’s are still pretty much a mystery.
In fact, many people get Alzheimer’s even though they lack the gene variant we know can play a role in the disease. This is a critical knowledge gap for research to address because the vast majority of Alzheimer’s patients don’t have this variant.
A new study provides key insights into what’s causing the disease. The research, published in Nature Communications, points to a breakdown over time in the brain’s system for clearing waste, an issue that seems to happen in some people as they get older.
Michael Glickman, a biologist at Technion – Israel Institute of Technology, helped lead this research. I asked him to tell me about his approach to studying how this breakdown occurs in the brain, and how he tested a treatment that has potential to fix the problem at its earliest stages.
Dr. Michael Glickman is internationally renowned for his research on the ubiquitin-proteasome system (UPS), the brain's system for clearing the waste that is involved in diseases such as Huntington's, Alzheimer's, and Parkinson's. He is the head of the Lab for Protein Characterization in the Faculty of Biology at the Technion – Israel Institute of Technology. In the lab, Michael and his team focus on protein recycling and the ubiquitin-proteasome system, which protects against serious diseases like Alzheimer’s, Parkinson’s, cystic fibrosis, and diabetes. After earning his PhD at the University of California at Berkeley in 1994, Michael joined the Technion as a Senior Lecturer in 1998 and has served as a full professor since 2009.
Dr. Michael Glickman