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.
New device finds breast cancer like earthquake detection
Mammograms are necessary breast cancer checks for women as they reach the recommended screening age between 40 and 50 years. Yet, many find the procedure uncomfortable. “I have large breasts, and to be able to image the full breast, the radiographer had to manipulate my breast within the machine, which took time and was quite uncomfortable,” recalls Angela, who preferred not to disclose her last name.
Breast cancer is the most widespread cancer in the world, affecting 2.3 million women in 2020. Screening exams such as mammograms can help find breast cancer early, leading to timely diagnosis and treatment. If this type of cancer is detected before the disease has spread, the 5-year survival rate is 99 percent. But some women forgo mammograms due to concerns about radiation or painful compression of breasts. Other issues, such as low income and a lack of access to healthcare, can also serve as barriers, especially for underserved populations.
Researchers at the University of Canterbury and startup Tiro Medical in Christchurch, New Zealand are hoping their new device—which doesn’t involve any radiation or compression of the breasts—could increase the accuracy of breast cancer screening, broaden access and encourage more women to get checked. They’re digging into clues from the way buildings move in an earthquake to help detect more cases of this disease.
Earthquake engineering inspires new breast cancer screening tech
What’s underneath a surface affects how it vibrates. Earthquake engineers look at the vibrations of swaying buildings to identify the underlying soil and tissue properties. “As the vibration wave travels, it reflects the stiffness of the material between that wave and the surface,” says Geoff Chase, professor of engineering at the University of Canterbury in Christchurch, New Zealand.
Chase is applying this same concept to breasts. Analyzing the surface motion of the breast as it vibrates could reveal the stiffness of the tissues underneath. Regions of high stiffness could point to cancer, given that cancerous breast tissue can be up to 20 times stiffer than normal tissue. “If in essence every woman’s breast is soft soil, then if you have some granite rocks in there, we’re going to see that on the surface,” explains Chase.
The earthquake-inspired device exceeds the 87 percent sensitivity of a 3D mammogram.
That notion underpins a new breast screening device, the brainchild of Chase. Women lie face down, with their breast being screened inside a circular hole and the nipple resting on a small disc called an actuator. The actuator moves up and down, between one and two millimeters, so there’s a small vibration, “almost like having your phone vibrate on your nipple,” says Jessica Fitzjohn, a postdoctoral fellow at the University of Canterbury who collaborated on the device design with Chase.
Cameras surrounding the device take photos of the breast surface motion as it vibrates. The photos are fed into image processing algorithms that convert them into data points. Then, diagnostic algorithms analyze those data points to find any differences in the breast tissue. “We’re looking for that stiffness contrast which could indicate a tumor,” Fitzjohn says.
A nascent yet promising technology
The device has been tested in a clinical trial of 14 women: one with healthy breasts and 13 with a tumor in one breast. The cohort was small but diverse, varying in age, breast volume and tumor size.
Results from the trial yielded a sensitivity rate, or the likelihood of correctly detecting breast cancer, of 85 percent. Meanwhile, the device’s specificity rate, or the probability of diagnosing healthy breasts, was 77 percent. By combining and optimizing certain diagnostic algorithms, the device reached between 92 and 100 percent sensitivity and between 80 and 86 percent specificity, which is comparable to the latest 3D mammogram technology. Called tomosynthesis, these 3D mammograms take a number of sharper, clearer and more detailed 3D images compared to the single 2D image of a conventional mammogram, and have a specificity score of 92 percent. Although the earthquake-inspired device’s specificity is lower, it exceeds the 87 percent sensitivity of a 3D mammogram.
The team hopes that cameras with better resolution can help improve the numbers. And with a limited amount of data in the first trial, the researchers are looking into funding for another clinical trial to validate their results on a larger cohort size.
Additionally, during the trial, the device correctly identified one woman’s breast as healthy, while her prior mammogram gave a false positive. The device correctly identified it as being healthy tissue. It was also able to capture the tiniest tumor at 7 millimeters—around a third of an inch or half as long as an aspirin tablet.
Diagnostic findings from the device are immediate.
When using the earthquake-inspired device, women lie face down, with their breast being screened inside circular holes.
University of Canterbury.
But more testing is needed to “prove the device’s ability to pick up small breast cancers less than 10 to 15 millimeters in size, as we know that finding cancers when they are small is the best way of improving outcomes,” says Richard Annand, a radiologist at Pacific Radiology in New Zealand. He explains that mammography already detects most precancerous lesions, so if the device will only be able to find large masses or lumps it won’t be particularly useful. While not directly involved in administering the clinical trial for the device, Annand was a director at the time for Canterbury Breastcare, where the trial occurred.
Meanwhile, Monique Gary, a breast surgical oncologist and medical director of the Grand View Health Cancer program in Pennsylvania, U.S., is excited to see new technologies advancing breast cancer screening and early detection. But she notes that the device may be challenging for “patients who are unable to lay prone, such as pregnant women as well as those who are differently abled, and this machine might exclude them.” She adds that it would also be interesting to explore how breast implants would impact the device’s vibrational frequency.
Diagnostic findings from the device are immediate, with the results available “before you put your clothes back on,” Chase says. The absence of any radiation is another benefit, though Annand considers it a minor edge “as we know the radiation dose used in mammography is minimal, and the advantages of having a mammogram far outweigh the potential risk of radiation.”
The researchers also conducted a separate ergonomic trial with 40 women to assess the device’s comfort, safety and ease of use. Angela was part of that trial and described the experience as “easy, quick, painless and required no manual intervention from an operator.” And if a person is uncomfortable being topless or having their breasts touched by someone else, “this type of device would make them more comfortable and less exposed,” she says.
While mammograms remain “the ‘gold standard’ in breast imaging, particularly screening, physicians need an option that can be used in combination with mammography.
Fitzjohn acknowledges that “at the moment, it’s quite a crude prototype—it’s just a block that you lie on.” The team prioritized function over form initially, but they’re now planning a few design improvements, including more cushioning for the breasts and the surface where the women lie on.
While mammograms remains “the ‘gold standard’ in breast imaging, particularly screening, physicians need an option that is good at excluding breast cancer when used in combination with mammography, has good availability, is easy to use and is affordable. There is the possibility that the device could fill this role,” Annand says.
Indeed, the researchers envision their new breast screening device as complementary to mammograms—a prescreening tool that could make breast cancer checks widely available. As the device is portable and doesn’t require specialized knowledge to operate, it can be used in clinics, pop-up screening facilities and rural communities. “If it was easily accessible, particularly as part of a checkup with a [general practitioner] or done in a practice the patient is familiar with, it may encourage more women to access this service,” Angela says. For those who find regular mammograms uncomfortable or can’t afford them, the earthquake-inspired device may be an option—and an even better one.
Broadening access could prompt more women to go for screenings, particularly younger women at higher risk of getting breast cancer because of a family history of the disease or specific gene mutations. “If we can provide an option for them then we can catch those cancers earlier,” Fitzjohn syas. “By taking screening to people, we’re increasing patient-centric care.”
With the team aiming to lower the device’s cost to somewhere between five and eight times less than mammography equipment, it would also be valuable for low-to-middle-income nations that are challenged to afford the infrastructure for mammograms or may not have enough skilled radiologists.
For Fitzjohn, the ultimate goal is to “increase equity in breast screening and catch cancer early so we have better outcomes for women who are diagnosed with breast cancer.”
Stronger psychedelics that rewire the brain, with Doug Drysdale
A promising development in science in recent years has been the use technology to optimize something natural. One-upping nature's wisdom isn't easy. In many cases, we haven't - and maybe we can't - figure it out. But today's episode features a fascinating example: using tech to optimize psychedelic mushrooms.
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These mushrooms have been used for religious, spiritual and medicinal purposes for thousands of years, but only in the past several decades have scientists brought psychedelics into the lab to enhance them and maximize their therapeutic value.
Today’s podcast guest, Doug Drysdale, is doing important work to lead this effort. Drysdale is the CEO of a company called Cybin that has figured out how to make psilocybin more potent, so it can be administered in smaller doses without side effects.
The natural form of psilocybin has been studied increasingly in the realm of mental health. Taking doses of these mushrooms appears to help people with anxiety and depression by spurring the development of connections in the brain, an example of neuroplasticity. The process basically shifts the adult brain from being fairly rigid like dried clay into a malleable substance like warm wax - the state of change that's constantly underway in the developing brains of children.
Neuroplasticity in adults seems to unlock some of our default ways of of thinking, the habitual thought patterns that’ve been associated with various mental health problems. Some promising research suggests that psilocybin causes a reset of sorts. It makes way for new, healthier thought patterns.
So what is Drysdale’s secret weapon to bring even more therapeutic value to psilocybin? It’s a process called deuteration. It focuses on the hydrogen atoms in psilocybin. These atoms are very light and don’t stick very well to carbon, which is another atom in psilocybin. As a result, our bodies can easily breaks down the bonds between the hydrogen and carbon atoms. For many people, that means psilocybin gets cleared from the body too quickly, before it can have a therapeutic benefit.
In deuteration, scientists do something simple but ingenious: they replace the hydrogen atoms with a molecule called deuterium. It’s twice as heavy as hydrogen and forms tighter bonds with the carbon. Because these pairs are so rock-steady, they slow down the rate at which psilocybin is metabolized, so it has more sustained effects on our brains.
Cybin isn’t Drysdale’s first go around at this - far from it. He has over 30 years of experience in the healthcare sector. During this time he’s raised around $4 billion of both public and private capital, and has been named Ernst and Young Entrepreneur of the Year. Before Cybin, he was the founding CEO of a pharmaceutical company called Alvogen, leading it from inception to around $500 million in revenues, across 35 countries. Drysdale has also been the head of mergers and acquisitions at Actavis Group, leading 15 corporate acquisitions across three continents.
In this episode, Drysdale walks us through the promising research of his current company, Cybin, and the different therapies he’s developing for anxiety and depression based not just on psilocybin but another psychedelic compound found in plants called DMT. He explains how they seem to have such powerful effects on the brain, as well as the potential for psychedelics to eventually support other use cases, including helping us strive toward higher levels of well-being. He goes on to discuss his views on mindfulness and lifestyle factors - such as optimal nutrition - that could help bring out hte best in psychedelics.
Show links:
Doug Drysdale full bio
Doug Drysdale twitter
Cybin website
Cybin development pipeline
Cybin's promising phase 2 research on depression
Johns Hopkins psychedelics research and psilocybin research
Mets owner Steve Cohen invests in psychedelic therapies
Doug Drysdale, CEO of Cybin