Your Digital Avatar May One Day Get Sick Before You Do
Artificial neurons in a concept of artificial intelligence.
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.
New Blood Test Can Detect Lymphoma Cells Before a Tumor Grows Back
David Kurtz making DNA sequencing libraries in his lab.
When David M. Kurtz was doing his clinical fellowship at Stanford University Medical Center in 2009, specializing in lymphoma treatments, he found himself grappling with a question no one could answer. A typical regimen for these blood cancers prescribed six cycles of chemotherapy, but no one knew why. "The number seemed to be drawn out of a hat," Kurtz says. Some patients felt much better after just two doses, but had to endure the toxic effects of the entire course. For some elderly patients, the side effects of chemo are so harsh, they alone can kill. Others appeared to be cancer-free on the CT scans after the requisite six but then succumbed to it months later.
"Anecdotally, one patient decided to stop therapy after one dose because he felt it was so toxic that he opted for hospice instead," says Kurtz, now an oncologist at the center. "Five years down the road, he was alive and well. For him, just one dose was enough." Others would return for their one-year check up and find that their tumors grew back. Kurtz felt that while CT scans and MRIs were powerful tools, they weren't perfect ones. They couldn't tell him if there were any cancer cells left, stealthily waiting to germinate again. The scans only showed the tumor once it was back.
Blood cancers claim about 68,000 people a year, with a new diagnosis made about every three minutes, according to the Leukemia Research Foundation. For patients with B-cell lymphoma, which Kurtz focuses on, the survival chances are better than for some others. About 60 percent are cured, but the remaining 40 percent will relapse—possibly because they will have a negative CT scan, but still harbor malignant cells. "You can't see this on imaging," says Michael Green, who also treats blood cancers at University of Texas MD Anderson Medical Center.
The new blood test is sensitive enough to spot one cancerous perpetrator amongst one million other DNA molecules.
Kurtz wanted a better diagnostic tool, so he started working on a blood test that could capture the circulating tumor DNA or ctDNA. For that, he needed to identify the specific mutations typical for B-cell lymphomas. Working together with another fellow PhD student Jake Chabon, Kurtz finally zeroed-in on the tumor's genetic "appearance" in 2017—a pair of specific mutations sitting in close proximity to each other—a rare and telling sign. The human genome contains about 3 billion base pairs of nucleotides—molecules that compose genes—and in case of the B-cell lymphoma cells these two mutations were only a few base pairs apart. "That was the moment when the light bulb went on," Kurtz says.
The duo formed a company named Foresight Diagnostics, focusing on taking the blood test to the clinic. But knowing the tumor's mutational signature was only half the process. The other was fishing the tumor's DNA out of patients' bloodstream that contains millions of other DNA molecules, explains Chabon, now Foresight's CEO. It would be like looking for an escaped criminal in a large crowd. Kurtz and Chabon solved the problem by taking the tumor's "mug shot" first. Doctors would take the biopsy pre-treatment and sequence the tumor, as if taking the criminal's photo. After treatments, they would match the "mug shot" to all DNA molecules derived from the patient's blood sample to see if any molecular criminals managed to escape the chemo.
Foresight isn't the only company working on blood-based tumor detection tests, which are dubbed liquid biopsies—other companies such as Natera or ArcherDx developed their own. But in a recent study, the Foresight team showed that their method is significantly more sensitive in "fishing out" the cancer molecules than existing tests. Chabon says that this test can detect circulating tumor DNA in concentrations that are nearly 100 times lower than other methods. Put another way, it's sensitive enough to spot one cancerous perpetrator amongst one million other DNA molecules.
"It increases the sensitivity of detection and really catches most patients who are going to progress," says Green, the University of Texas oncologist who wasn't involved in the study, but is familiar with the method. It would also allow monitoring patients during treatment and making better-informed decisions about which therapy regimens would be most effective. "It's a minimally invasive test," Green says, and "it gives you a very high confidence about what's going on."
Having shown that the test works well, Kurtz and Chabon are planning a new trial in which oncologists would rely on their method to decide when to stop or continue chemo. They also aim to extend their test to detect other malignancies such as lung, breast or colorectal cancers. The latest genome sequencing technologies have sequenced and catalogued over 2,500 different tumor specimens and the Foresight team is analyzing this data, says Chabon, which gives the team the opportunity to create more molecular "mug shots."
The team hopes that that their blood cancer test will become available to patients within about five years, making doctors' job easier, and not only at the biological level. "When I tell patients, "good news, your cancer is in remission', they ask me, 'does it mean I'm cured?'" Kurtz says. "Right now I can't answer this question because I don't know—but I would like to." His company's test, he hopes, will enable him to reply with certainty. He'd very much like to have the power of that foresight.
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
The First Mass-Produced Solar Car Is Coming Soon, Sparking Excitement and Uncertainty
Reporter Michaela Haas takes Aptera's Sol car out for a test drive in San Diego, Calif.
The white two-seater car that rolls down the street in the Sorrento Valley of San Diego looks like a futuristic batmobile, with its long aerodynamic tail and curved underbelly. Called 'Sol' (Spanish for "sun"), it runs solely on solar and could be the future of green cars. Its maker, the California startup Aptera, has announced the production of Sol, the world's first mass-produced solar vehicle, by the end of this year. Aptera co-founder Chris Anthony points to the sky as he says, "On this sunny California day, there is ample fuel. You never need to charge the car."
If you live in a sunny state like California or Florida, you might never need to plug in the streamlined Sol because the solar panels recharge while driving and parked. Its 60-mile range is more than the average commuter needs. For cloudy weather, battery packs can be recharged electronically for a range of up to 1,000 miles. The ultra-aerodynamic shape made of lightweight materials such as carbon, Kevlar, and hemp makes the Sol four times more energy-efficient than a Tesla, according to Aptera. "The material is seven times stronger than steel and even survives hail or an angry ex-girlfriend," Anthony promises.
Co-founder Steve Fambro opens the Sol's white doors that fly upwards like wings and I get inside for a test drive. Two dozen square solar panels, each the size of a large square coaster, on the roof, front, and tail power the car. The white interior is spartan; monitors have replaced mirrors and the dashboard. An engineer sits in the driver's seat, hits the pedal, and the low-drag two-seater zooms from 0 to 60 in 3.5 seconds.
It feels like sitting in a race car because the two-seater is so low to the ground but the car is built to go no faster than 100 or 110 mph. The finished car will weigh less than 1,800 pounds, about half of the smallest Tesla. The average car, by comparison, weighs more than double that. "We've built it primarily for energy efficiency," Steve Fambro says, explaining why the Sol has only three wheels. It's technically an "auto-cycle," a hybrid between a motorcycle and a car, but Aptera's designers are also working to design a four-seater.
There has never been a lack of grand visions for the future of the automobile, but until these solar cars actually hit the streets, nobody knows how the promises will hold up.
Transportation is currently the biggest source of greenhouse gases. Developing an efficient solar car that does not burden the grid has been the dream of innovators for decades. Every other year, dozens of innovators race their self-built solar cars 2,000 miles through the Australian desert.
More effective solar panels are finally making the dream mass-compatible, but just like other innovative car ideas, Aptera's vision has been plagued with money problems. Anthony and Fambro were part of the original crew that founded Aptera in 2006 and worked on the first prototype around the same time Tesla built its first roadster, but Aptera went bankrupt in 2011. Anthony and Fambro left a year before the bankruptcy and went on to start other companies. Among other projects, Fambro developed the first USDA organic vertical farm in the United Arab Emirates, and Anthony built a lithium battery company, before the two decided to buy Aptera back. Without a billionaire such as Elon Musk bankrolling the risky process of establishing a whole new car production system from scratch, the huge production costs are almost insurmountable.
But Aptera's founders believe they have found solutions for the entire production process as well as the car design. Most parts of the Sol's body can be made by 3D printers and assembled like a Lego kit. If this makes you think of a toy car, Anthony assures potential buyers that the car aced stress tests and claims it's safer than any vehicle on the market, "because the interior is shaped like an egg and if there is an impact, the pressure gets distributed equally." However, Aptera has yet to release crash test safety data so outside experts cannot evaluate their claims.
Instead of building a huge production facility, Anthony and Fambro envision "micro-factories," each less than 10,000 square feet, where a small crew can assemble cars on demand wherever the orders are highest, be it in California, Canada, or China.
If a part of the Sol breaks, Aptera promises to send replacement parts to any corner of the world within 24 hours, with instructions. So a mechanic in a rural corner in Arkansas or China who never worked on a solar car before simply needs to download the instructions and replace the broken part. At least that's the idea. "The material does not rust nor fatigue," Fambro promises. "You can pass the car onto your grandchildren. When more efficient solar panels hit the market, we simply replace them."
More than 11,000 potential buyers have already signed up; the cheapest model costs around $26,000 USD and Aptera expects the first cars to ship by the end of the year.
Two other solar carmakers are vying for the pole position in the race to be the first to market: The German startup Sono has also announced it will also produce its first solar car by the end of this year. The price tag for the basic model is also around $26,000, but its concept is very different. From the outside, the Sion looks like a conservative minivan for a family; only a closer look reveals that the dark exterior is made of solar panels. Sono, too, nearly went bankrupt a few years ago and was saved through a crowdfunding campaign by enthusiastic fans.
Meanwhile, Norwegian company Lightyear wants to produce a sleek solar-powered luxury sedan by the end of the year, but its price of around $180,000 makes it unaffordable for most buyers.
There has never been a lack of grand visions for the future of the automobile, but until these solar cars actually hit the streets, nobody knows how the promises will hold up. How often will the cars need to be repaired? What happens when snow and ice cover the solar panels? Also, you can't park the car in a garage if you need the sun to charge it.
Critics, including students at the Solar Car team at the University of Michigan, say that mounting solar panels on a moving vehicle will never yield the most efficient results compared to static panels. Also, they are quick to point out that no company has managed to overcome the production hurdles yet. Others in the field also wonder how well the solar panels will actually work.
"It's important to realize that the solar mileage claims by these companies are likely the theoretical best case scenario but in the real world, solar range will be significantly less when you factor in shading, parking in garages, and geographies with lower solar irradiance," says Evan Stumpges, the team coordinator for the American Solar Challenge, a competition in which enthusiasts build and race solar-powered cars. "The encouraging thing is that I have seen videos of real working prototypes for each of these vehicles which is a key accomplishment. That said, I believe the biggest hurdle these companies have yet to face is successfully ramping up to volume production and understanding what their profitability point will be for selling the vehicles once production has stabilized."
Professor Daniel M. Kammen, the founding director of the Renewable and Appropriate Energy Laboratory at the University of California, Berkeley, and one of the world's foremost experts on renewable energy, believes that the technical challenges have been solved, and that solar cars have real advantages over electric vehicles.
"This is the right time to be bullish. Cutting out the charging is a natural solution for long rides," he says. "These vehicles are essentially solar panels and batteries on wheels. These are now record low-cost and can be built from sustainable materials." Apart from Aptera's no-charge technology, he appreciates the move toward no-conflict materials. "Not only is the time ripe but the youth movement is pushing toward conflict-free material and reducing resource waste....A low-cost solar fleet could be really interesting in relieving burden on the grid, or you could easily imagine a city buying a bunch of them and connecting them with mass transit." While he has followed all three new solar companies with interest, he has already ordered an Aptera car for himself, "because it's American and it looks the most different."
After taking a spin in the Sol, it is startling to switch back into a regular four-seater. Rolling out of Aptera's parking lot onto the freeway next to all the oversized gas guzzlers that need to stop every couple of hundreds of miles to fill up, one can't help but think: We've just taken a trip into the future.