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.
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
How the body's immune resilience affects our health and lifespan
Story by Big Think
It is a mystery why humans manifest vast differences in lifespan, health, and susceptibility to infectious diseases. However, a team of international scientists has revealed that the capacity to resist or recover from infections and inflammation (a trait they call “immune resilience”) is one of the major contributors to these differences.
Immune resilience involves controlling inflammation and preserving or rapidly restoring immune activity at any age, explained Weijing He, a study co-author. He and his colleagues discovered that people with the highest level of immune resilience were more likely to live longer, resist infection and recurrence of skin cancer, and survive COVID and sepsis.
Measuring immune resilience
The researchers measured immune resilience in two ways. The first is based on the relative quantities of two types of immune cells, CD4+ T cells and CD8+ T cells. CD4+ T cells coordinate the immune system’s response to pathogens and are often used to measure immune health (with higher levels typically suggesting a stronger immune system). However, in 2021, the researchers found that a low level of CD8+ T cells (which are responsible for killing damaged or infected cells) is also an important indicator of immune health. In fact, patients with high levels of CD4+ T cells and low levels of CD8+ T cells during SARS-CoV-2 and HIV infection were the least likely to develop severe COVID and AIDS.
Individuals with optimal levels of immune resilience were more likely to live longer.
In the same 2021 study, the researchers identified a second measure of immune resilience that involves two gene expression signatures correlated with an infected person’s risk of death. One of the signatures was linked to a higher risk of death; it includes genes related to inflammation — an essential process for jumpstarting the immune system but one that can cause considerable damage if left unbridled. The other signature was linked to a greater chance of survival; it includes genes related to keeping inflammation in check. These genes help the immune system mount a balanced immune response during infection and taper down the response after the threat is gone. The researchers found that participants who expressed the optimal combination of genes lived longer.
Immune resilience and longevity
The researchers assessed levels of immune resilience in nearly 50,000 participants of different ages and with various types of challenges to their immune systems, including acute infections, chronic diseases, and cancers. Their evaluation demonstrated that individuals with optimal levels of immune resilience were more likely to live longer, resist HIV and influenza infections, resist recurrence of skin cancer after kidney transplant, survive COVID infection, and survive sepsis.
However, a person’s immune resilience fluctuates all the time. Study participants who had optimal immune resilience before common symptomatic viral infections like a cold or the flu experienced a shift in their gene expression to poor immune resilience within 48 hours of symptom onset. As these people recovered from their infection, many gradually returned to the more favorable gene expression levels they had before. However, nearly 30% who once had optimal immune resilience did not fully regain that survival-associated profile by the end of the cold and flu season, even though they had recovered from their illness.
Intriguingly, some people who are 90+ years old still have optimal immune resilience, suggesting that these individuals’ immune systems have an exceptional capacity to control inflammation and rapidly restore proper immune balance.
This could suggest that the recovery phase varies among people and diseases. For example, young female sex workers who had many clients and did not use condoms — and thus were repeatedly exposed to sexually transmitted pathogens — had very low immune resilience. However, most of the sex workers who began reducing their exposure to sexually transmitted pathogens by using condoms and decreasing their number of sex partners experienced an improvement in immune resilience over the next 10 years.
Immune resilience and aging
The researchers found that the proportion of people with optimal immune resilience tended to be highest among the young and lowest among the elderly. The researchers suggest that, as people age, they are exposed to increasingly more health conditions (acute infections, chronic diseases, cancers, etc.) which challenge their immune systems to undergo a “respond-and-recover” cycle. During the response phase, CD8+ T cells and inflammatory gene expression increase, and during the recovery phase, they go back down.
However, over a lifetime of repeated challenges, the immune system is slower to recover, altering a person’s immune resilience. Intriguingly, some people who are 90+ years old still have optimal immune resilience, suggesting that these individuals’ immune systems have an exceptional capacity to control inflammation and rapidly restore proper immune balance despite the many respond-and-recover cycles that their immune systems have faced.
Public health ramifications could be significant. Immune cell and gene expression profile assessments are relatively simple to conduct, and being able to determine a person’s immune resilience can help identify whether someone is at greater risk for developing diseases, how they will respond to treatment, and whether, as well as to what extent, they will recover.