Your Digital Avatar May One Day Get Sick Before You Do

Your Digital Avatar May One Day Get Sick Before You Do

Artificial neurons in a concept of artificial intelligence.

(© ktsdesign/Fotolia)



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.

Noah Davis
Noah Davis is a writer living in Brooklyn. Visit his website at http://www.noahedavis.com.
New study: Hotter nights, climate change, cause sleep loss with some affected more than others

According to a new study, sleep is impaired with temperatures over 50 degrees, and temps higher than 77 degrees reduce the chances of getting seven hours.

Photo by Altınay Dinç on Unsplash

Data from the National Sleep Foundation finds that the optimal bedroom temperature for sleep is around 65 degrees Fahrenheit. But we may be getting fewer hours of "good sleepin’ weather" as the climate warms, according to a recent paper from researchers at the University of Copenhagen, Denmark.

Published in One Earth, the study finds that heat related to climate change could provide a “pathway” to sleep deprivation. The authors say the effect is “substantially larger” for those in lower-income countries. Hours of sleep decline when nighttime temperature exceeds 50 degrees, and temps higher than 77 reduce the chances of sleeping for seven hours by 3.5 percent. Even small losses associated with rising temperatures contribute significantly to people not getting enough sleep.

We’re affected by high temperatures at night because body temperature becomes more sensitive to the environment when slumbering. “Mechanisms that control for thermal regulation become more disordered during sleep,” explains Clete Kushida, a neurologist, professor of psychiatry at Stanford University and sleep medicine clinician.

The study finds that women and older adults are especially vulnerable. Worldwide, the elderly lost over twice as much sleep per degree of warming compared to younger people. This phenomenon was apparent between the ages of 60 and 70, and it increased beyond age 70. “The mechanism for balancing temperatures appears to be more affected with age,” Kushida adds.

Keep Reading Keep Reading
Sherree Geyer
Sherree Geyer is a freelance health journalist. She regularly writes for “Pain Medicine News,” “Pharmacy Practice News” and other trade publications. A member of the Association of Healthcare Journalists, National Association of Science Writers and National Writers Union, she holds a bachelor’s degree in journalism from Northern Illinois University.
Why we need to get serious about ending aging

With the population of older people projected to grow dramatically, and the cost of healthcare with it, the future welfare of the country may depend on solving aging, writes philosopher Ingemar Patrick Linden.

Photo by Alessio Lin on Unsplash

It is widely acknowledged that even a small advance in anti-aging science could yield benefits in terms of healthy years that the traditional paradigm of targeting specific diseases is not likely to produce. A more youthful population would also be less vulnerable to epidemics. Approximately 93 percent of all COVID-19 deaths reported in the U.S. occurred among those aged 50 or older. The potential economic benefits would be tremendous. A more youthful population would consume less medical resources and be able to work longer. A recent study published in Nature estimates that a slowdown in aging that increases life expectancy by one year would save $38 trillion per year for the U.S. alone.

A societal effort to understand, slow down, arrest or even reverse aging of at least the size of our response to COVID-19 would therefore be a rational commitment. In fact, given that America’s older population is projected to grow dramatically, and the cost of healthcare with it, it is not an overstatement to say that the future welfare of the country may depend on solving aging.

This year, the kingdom of Saudi Arabia has announced that it will spend up to 1 billion dollars per year on science with the potential to slow down the aging process. We have also seen important investments from billionaires like Google co-founder Larry Page, Amazon founder Jeff Bezos, business magnate Larry Ellison, and PayPal co-founder Peter Thiel.

The U.S. government, however, is lagging: The National Institutes of Health spent less than one percent of its $43 billion budget for the fiscal year of 2021 on the National Institute on Aging’s Division of Aging Biology. When you visit the division’s webpage you find that their mission statement carefully omits any mention of the possibility of slowing down the aging process.

Keep Reading Keep Reading
Ingemar Patrick Linden
Driven by a passion to probe the fundamental questions we are confronted with, Dr. INGEMAR PATRICK LINDEN has been on a journey of discovery taking him from Lund University in Sweden, to UCL in London, to University of California, to New York, where he has taught philosophy for almost a decade. Death. It does not get more fundamental than that. One of the ideas that has remained a firm conviction of the author’s since childhood is that we do not have enough time. We are but the beginnings of complete humans, fragments of what we could be. It was the realization that not all share this view, in fact, surveys show that most do not, that inspired, and necessitated, the writing of THE CASE AGAINST DEATH.