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.
Researchers claimed they built a breakthrough superconductor. Social media shot it down almost instantly.
Harsh Mathur was a graduate physics student at Yale University in late 1989 when faculty announced they had failed to replicate claims made by scientists at the University of Utah and the University of Wolverhampton in England.
Such work is routine. Replicating or attempting to replicate the contraptions, calculations and conclusions crafted by colleagues is foundational to the scientific method. But in this instance, Yale’s findings were reported globally.
“I had a ringside view, and it was crazy,” recalls Mathur, now a professor of physics at Case Western Reserve University in Ohio.
Yale’s findings drew so much attention because initial experiments by Stanley Pons of Utah and Martin Fleischmann of Wolverhampton led to a startling claim: They were able to fuse atoms at room temperature – a scientific El Dorado known as “cold fusion.”
Nuclear fusion powers the stars in the universe. However, star cores must be at least 23.4 million degrees Fahrenheit and under extraordinary pressure to achieve fusion. Pons and Fleischmann claimed they had created an almost limitless source of power achievable at any temperature.
Like fusion, superconductivity can only be achieved in mostly impractical circumstances.
But about six months after they made their startling announcement, the pair’s findings were discredited by researchers at Yale and the California Institute of Technology. It was one of the first instances of a major scientific debunking covered by mass media.
Some scholars say the media attention for cold fusion stemmed partly from a dazzling announcement made three years prior in 1986: Scientists had created the first “superconductor” – material that could transmit electrical current with little or no resistance. It drew global headlines – and whetted the public’s appetite for announcements of scientific breakthroughs that could cause economic transformations.
But like fusion, superconductivity can only be achieved in mostly impractical circumstances: It must operate either at temperatures of at least negative 100 degrees Fahrenheit, or under pressures of around 150,000 pounds per square inch. Superconductivity that functions in closer to a normal environment would cut energy costs dramatically while also opening infinite possibilities for computing, space travel and other applications.
In July, a group of South Korean scientists posted material claiming they had created an iron crystalline substance called LK-99 that could achieve superconductivity at slightly above room temperature and at ambient pressure. The group partners with the Quantum Energy Research Centre, a privately-held enterprise in Seoul, and their claims drew global headlines.
Their work was also debunked. But in the age of internet and social media, the process was compressed from half-a-year into days. And it did not require researchers at world-class universities.
One of the most compelling critiques came from Derrick VanGennep. Although he works in finance, he holds a Ph.D. in physics and held a postdoctoral position at Harvard. The South Korean researchers had posted a video of a nugget of LK-99 in what they claimed was the throes of the Meissner effect – an expulsion of the substance’s magnetic field that would cause it to levitate above a magnet. Unless Hollywood magic is involved, only superconducting material can hover in this manner.
That claim made VanGennep skeptical, particularly since LK-99’s levitation appeared unenthusiastic at best. In fact, a corner of the material still adhered to the magnet near its center. He thought the video demonstrated ferromagnetism – two magnets repulsing one another. He mixed powdered graphite with super glue, stuck iron filings to its surface and mimicked the behavior of LK-99 in his own video, which was posted alongside the researchers’ video.
VanGennep believes the boldness of the South Korean claim was what led to him and others in the scientific community questioning it so quickly.
“The swift replication attempts stemmed from the combination of the extreme claim, the fact that the synthesis for this material is very straightforward and fast, and the amount of attention that this story was getting on social media,” he says.
But practicing scientists were suspicious of the data as well. Michael Norman, director of the Argonne Quantum Institute at the Argonne National Laboratory just outside of Chicago, had doubts immediately.
Will this saga hurt or even affect the careers of the South Korean researchers? Possibly not, if the previous fusion example is any indication.
“It wasn’t a very polished paper,” Norman says of the Korean scientists’ work. That opinion was reinforced, he adds, when it turned out the paper had been posted online by one of the researchers prior to seeking publication in a peer-reviewed journal. Although Norman and Mathur say that is routine with scientific research these days, Norman notes it was posted by one of the junior researchers over the doubts of two more senior scientists on the project.
Norman also raises doubts about the data reported. Among other issues, he observes that the samples created by the South Korean researchers contained traces of copper sulfide that could inadvertently amplify findings of conductivity.
The lack of the Meissner effect also caught Mathur’s attention. “Ferromagnets tend to be unstable when they levitate,” he says, adding that the video “just made me feel unconvinced. And it made me feel like they hadn't made a very good case for themselves.”
Will this saga hurt or even affect the careers of the South Korean researchers? Possibly not, if the previous fusion example is any indication. Despite being debunked, cold fusion claimants Pons and Fleischmann didn’t disappear. They moved their research to automaker Toyota’s IMRA laboratory in France, which along with the Japanese government spent tens of millions of dollars on their work before finally pulling the plug in 1998.
Fusion has since been created in laboratories, but being unable to reproduce the density of a star’s core would require excruciatingly high temperatures to achieve – about 160 million degrees Fahrenheit. A recently released Government Accountability Office report concludes practical fusion likely remains at least decades away.
However, like Pons and Fleischman, the South Korean researchers are not going anywhere. They claim that LK-99’s Meissner effect is being obscured by the fact the substance is both ferromagnetic and diamagnetic. They have filed for a patent in their country. But for now, those claims remain chimerical.
In the meantime, the consensus as to when a room temperature superconductor will be achieved is mixed. VenGennep – who studied the issue during his graduate and postgraduate work – puts the chance of creating such a superconductor by 2050 at perhaps 50-50. Mathur believes it could happen sooner, but adds that research on the topic has been going on for nearly a century, and that it has seen many plateaus.
“There's always this possibility that there's going to be something out there that we're going to discover unexpectedly,” Norman notes. The only certainty in this age of social media is that it will be put through the rigors of replication instantly.
Scientists implant brain cells to counter Parkinson's disease
Martin Taylor was only 32 when he was diagnosed with Parkinson's, a disease that causes tremors, stiff muscles and slow physical movement - symptoms that steadily get worse as time goes on.
“It's horrible having Parkinson's,” says Taylor, a data analyst, now 41. “It limits my ability to be the dad and husband that I want to be in many cruel and debilitating ways.”
Today, more than 10 million people worldwide live with Parkinson's. Most are diagnosed when they're considerably older than Taylor, after age 60. Although recent research has called into question certain aspects of the disease’s origins, Parkinson’s eventually kills the nerve cells in the brain that produce dopamine, a signaling chemical that carries messages around the body to control movement. Many patients have lost 60 to 80 percent of these cells by the time they are diagnosed.
For years, there's been little improvement in the standard treatment. Patients are typically given the drug levodopa, a chemical that's absorbed by the brain’s nerve cells, or neurons, and converted into dopamine. This drug addresses the symptoms but has no impact on the course of the disease as patients continue to lose dopamine producing neurons. Eventually, the treatment stops working effectively.
BlueRock Therapeutics, a cell therapy company based in Massachusetts, is taking a different approach by focusing on the use of stem cells, which can divide into and generate new specialized cells. The company makes the dopamine-producing cells that patients have lost and inserts these cells into patients' brains. “We have a disease with a high unmet need,” says Ahmed Enayetallah, the senior vice president and head of development at BlueRock. “We know [which] cells…are lost to the disease, and we can make them. So it really came together to use stem cells in Parkinson's.”
In a phase 1 research trial announced late last month, patients reported that their symptoms had improved after a year of treatment. Brain scans also showed an increased number of neurons generating dopamine in patients’ brains.
Increases in dopamine signals
The recent phase 1 trial focused on deploying BlueRock’s cell therapy, called bemdaneprocel, to treat 12 patients suffering from Parkinson’s. The team developed the new nerve cells and implanted them into specific locations on each side of the patient's brain through two small holes in the skull made by a neurosurgeon. “We implant cells into the places in the brain where we think they have the potential to reform the neural networks that are lost to Parkinson's disease,” Enayetallah says. The goal is to restore motor function to patients over the long-term.
Five patients were given a relatively low dose of cells while seven got higher doses. Specialized brain scans showed evidence that the transplanted cells had survived, increasing the overall number of dopamine producing cells. The team compared the baseline number of these cells before surgery to the levels one year later. “The scans tell us there is evidence of increased dopamine signals in the part of the brain affected by Parkinson's,” Enayetallah says. “Normally you’d expect the signal to go down in untreated Parkinson’s patients.”
"I think it has a real chance to reverse motor symptoms, essentially replacing a missing part," says Tilo Kunath, a professor of regenerative neurobiology at the University of Edinburgh.
The team also asked patients to use a specific type of home diary to log the times when symptoms were well controlled and when they prevented normal activity. After a year of treatment, patients taking the higher dose reported symptoms were under control for an average of 2.16 hours per day above their baselines. At the smaller dose, these improvements were significantly lower, 0.72 hours per day. The higher-dose patients reported a corresponding decrease in the amount of time when symptoms were uncontrolled, by an average of 1.91 hours, compared to 0.75 hours for the lower dose. The trial was safe, and patients tolerated the year of immunosuppression needed to make sure their bodies could handle the foreign cells.
Claire Bale, the associate director of research at Parkinson's U.K., sees the promise of BlueRock's approach, while noting the need for more research on a possible placebo effect. The trial participants knew they were getting the active treatment, and placebo effects are known to be a potential factor in Parkinson’s research. Even so, “The results indicate that this therapy produces improvements in symptoms for Parkinson's, which is very encouraging,” Bale says.
Tilo Kunath, a professor of regenerative neurobiology at the University of Edinburgh, also finds the results intriguing. “I think it's excellent,” he says. “I think it has a real chance to reverse motor symptoms, essentially replacing a missing part.” However, it could take time for this therapy to become widely available, Kunath says, and patients in the late stages of the disease may not benefit as much. “Data from cell transplantation with fetal tissue in the 1980s and 90s show that cells did not survive well and release dopamine in these [late-stage] patients.”
Searching for the right approach
There's a long history of using cell therapy as a treatment for Parkinson's. About four decades ago, scientists at the University of Lund in Sweden developed a method in which they transferred parts of fetal brain tissue to patients with Parkinson's so that their nerve cells would produce dopamine. Many benefited, and some were able to stop their medication. However, the use of fetal tissue was highly controversial at that time, and the tissues were difficult to obtain. Later trials in the U.S. showed that people benefited only if a significant amount of the tissue was used, and several patients experienced side effects. Eventually, the work lost momentum.
“Like many in the community, I'm aware of the long history of cell therapy,” says Taylor, the patient living with Parkinson's. “They've long had that cure over the horizon.”
In 2000, Lorenz Studer led a team at the Memorial Sloan Kettering Centre, in New York, to find the chemical signals needed to get stem cells to differentiate into cells that release dopamine. Back then, the team managed to make cells that produced some dopamine, but they led to only limited improvements in animals. About a decade later, in 2011, Studer and his team found the specific signals needed to guide embryonic cells to become the right kind of dopamine producing cells. Their experiments in mice, rats and monkeys showed that their implanted cells had a significant impact, restoring lost movement.
Studer then co-founded BlueRock Therapeutics in 2016. Forming the most effective stem cells has been one of the biggest challenges, says Enayetallah, the BlueRock VP. “It's taken a lot of effort and investment to manufacture and make the cells at the right scale under the right conditions.” The team is now using cells that were first isolated in 1998 at the University of Wisconsin, a major advantage because they’re available in a virtually unlimited supply.
Other efforts underway
In the past several years, University of Lund researchers have begun to collaborate with the University of Cambridge on a project to use embryonic stem cells, similar to BlueRock’s approach. They began clinical trials this year.
A company in Japan called Sumitomo is using a different strategy; instead of stem cells from embryos, they’re reprogramming adults' blood or skin cells into induced pluripotent stem cells - meaning they can turn into any cell type - and then directing them into dopamine producing neurons. Although Sumitomo started clinical trials earlier than BlueRock, they haven’t yet revealed any results.
“It's a rapidly evolving field,” says Emma Lane, a pharmacologist at the University of Cardiff who researches clinical interventions for Parkinson’s. “But BlueRock’s trial is the first full phase 1 trial to report such positive findings with stem cell based therapies.” The company’s upcoming phase 2 research will be critical to show how effectively the therapy can improve disease symptoms, she added.
The cure over the horizon
BlueRock will continue to look at data from patients in the phase 1 trial to monitor the treatment’s effects over a two-year period. Meanwhile, the team is planning the phase 2 trial with more participants, including a placebo group.
For patients with Parkinson’s like Martin Taylor, the therapy offers some hope, though Taylor recognizes that more research is needed.
BlueRock Therapeutics
“Like many in the community, I'm aware of the long history of cell therapy,” he says. “They've long had that cure over the horizon.” His expectations are somewhat guarded, he says, but, “it's certainly positive to see…movement in the field again.”
"If we can demonstrate what we’re seeing today in a more robust study, that would be great,” Enayetallah says. “At the end of the day, we want to address that unmet need in a field that's been waiting for a long time.”
Editor's note: The company featured in this piece, BlueRock Therapeutics, is a portfolio company of Leaps by Bayer, which is a sponsor of Leaps.org. BlueRock was acquired by Bayer Pharmaceuticals in 2019. Leaps by Bayer and other sponsors have never exerted influence over Leaps.org content or contributors.