Who’s Responsible for Curbing the Teen Vaping Epidemic?
A teenage girl vaping in a park.
E-cigarettes are big business. In 2017, American consumers bought more than $250 million in vapes and juice-filled pods, and spent $1 billion in 2018. By 2023, the global market could be worth $44 billion a year.
"My nine-year-old actually knows what Juuling is. In many cases the [school] bathroom is now referred to as 'the Juuling room.'"
Investors are trying to capitalize on the phenomenal growth. In July 2018, Juul Labs, the company that owns 70 percent of the U.S. e-cigarette market share, raised $1.25 billion at a $16 billion valuation, then sold a 35 percent stake to Phillip Morris USA owner Altria Group in December. The second transaction valued the company at $38 billion. While the traditional tobacco market remains much larger, it's projected to grow at less than two percent a year, making the attractiveness of the rapidly expanding e-cigarette market obvious.
While Juul and other e-cigarette manufacturers argue that their products help adults quit smoking – and there's some research to back this narrative up – much of the growth has been driven by children and teenagers. One CDC study showed a 48 percent rise in e-cigarette use by middle schoolers and a 78 percent increase by high schoolers between 2017 and 2018, a jump from 1.5 million kids to 3.6 million. In response to the study, F.D.A. Commissioner Scott Gottlieb said, "We see clear signs that youth use of electronic cigarettes has reached an epidemic proportion."
Another study found that teenagers between 15 and 17 were 16 times more likely to use Juul than people aged 25-34. In December, Surgeon General Jerome Adams said, "My nine-year-old actually knows what Juuling is. In many cases the [school] bathroom is now referred to as 'the Juuling room.'"
And the product is seriously addictive. A single Juul pod contains as much nicotine as a pack of 20 regular cigarettes. Considering that 90 percent of smokers are addicted by 18 years old, it's clear that steps need to be taken to combat the growing epidemic.
But who should take the lead? Juul and other e-cigarette companies? The F.D.A. and other government regulators? Schools? Parents?
The Surgeon General's website has a list of earnest possible texts that parents can send to their teens to dissuade them from Juuling, like: "Hope none of your friends use e-cigarettes around you. Even breathing the cloud they exhale can expose you to nicotine and chemicals that can be dangerous to your health." While parents can attempt to police their teens, many experts believe that the primary push should come at a federal level.
The regulation battle has already begun. In September, the F.D.A. announced that Juul had 60 days to show a plan that would prevent youth from getting their hands on the product. The result was for the company to announce that it wouldn't sell flavored pods in retail stores except for tobacco, menthol, and mint; Juul also shuttered its Instagram and Facebook accounts. These regulations mirrored an F.D.A. mandate two days later that required flavored e-cigarettes to be sold in closed-off areas. "This policy will make sure the fruity flavors are no longer accessible to kids in retail sites, plan and simple," Commissioner Gottlieb said when announcing the moves. "That's where they're getting access to the e-cigs and we intend to end those sales."
"There isn't a great history of the tobacco industry acting responsibly and being able to in any way police itself."
While so far, Gottlieb – who drew concerns about conflict of interest due to his past position as a board member at e-cigarette company, Kure – has pleased anti-smoking advocates with his efforts, some observers also argue that it needs to go further. "Overall, we didn't know what to expect when a new commissioner came in, but it's been quite refreshing how much attention has been paid to the tobacco industry by the F.D.A.," Robin Koval, CEO and president of Truth Initiative, said a day after the F.D.A. announced the proposed regulations. "It's important to have a start. I certainly want to give credit for that. But we were really hoping and feel that what was announced...doesn't go far enough."
The issue is the industry's inability or unwillingness to police itself in the past. Juul, however, claims that it's now proactively working to prevent young people from taking up its product. "Juul Labs and F.D.A. share a common goal – preventing youth from initiating on nicotine," a company representative said in an email. "To paraphrase Commissioner Gottlieb, we want to be the off-ramp for adult smokers to switch from cigarettes, not an on-ramp for America's youth to initiate on nicotine. We won't be successful in our mission to serve adult smokers if we don't narrow the on-ramp... Our intent was never to have youth use Juul products. But intent is not enough, the numbers are what matter, and the numbers tell us underage use of e-cigarette products is a problem. We must solve it."
Juul argues that its products help adults quit – even offering a calculator on the website showing how much people will save – and that it didn't target youth. But studies show otherwise. Furthermore, the youth smoking prevention curriculum the company released was poorly received. "It's what Philip Morris did years ago," said Bonnie Halpern-Felsher, a professor of pediatrics at Stanford who helped author a study on the program's faults. "They aren't talking about their named product. They are talking about vapes or e-cigarettes. Youth don't consider Juuls to be vapes or e-cigarettes. [Teens] don't talk about flavors. They don't talk about marketing. They did it to look good. But if you look at what [Juul] put together, it's a pretty awful curriculum that was put together pretty quickly."
The American Lung Association gave the FDA an "F" for failing to take mint and menthol e-cigs off the market, since those flavors remain popular with teens.
Add this all up, and in the end, it's hard to see the industry being able to police itself, critics say. Neither the past examples of other tobacco companies nor the present self-imposed regulations indicate that this will succeed.
"There isn't a great history of the tobacco industry acting responsibly and being able to in any way police itself," Koval said. "That job is best left to the F.D.A., and to the states and localities in what they can regulate and legislate to protect young people."
Halpern-Felsher agreed. "I think we need independent bodies. I really don't think that a voluntary ban or a regulation on the part of the industry is a good idea, nor do I think it will work," she said. "It's pretty much the same story, of repeating itself."
Just last week, the American Association of Pediatrics issued a new policy statement calling for the F.D.A. to immediately ban the sale of e-cigarettes to anyone under age 21 and to prohibit the online sale of vaping products and solutions, among other measures. And in its annual report, the American Lung Association gave the F.D.A. an "F" for failing to take mint and menthol e-cigs off the market, since those flavors remain popular with teens.
Few, if any people involved, want more regulation from the federal government. In an ideal world, this wouldn't be necessary. But many experts agree that it is. Anything else is just blowing smoke.
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.
The Brave New World of Using DNA to Store Data
A panoramic view of DNA
Netscape co-founder-turned-venture capitalist billionaire investor Marc Andreessen once posited that software was eating the world. He was right, and the takeover of software resulted in many things. One of them is data. Lots and lots and lots of data. In the previous two years, humanity created more data than it did during its entire existence combined, and the amount will only increase. Think about it: The hundreds of 50KB emails you write a day, the dozens of 10MB photos, the minute-long, 350MB 4K video you shoot on your iPhone X add up to vast quantities of information. All that information needs to be stored. And that's becoming an issue as data volume outpaces storage space.
The race is on to find another medium capable of storing massive amounts of information in as small a space as possible.
"There won't be enough silicon to store all the data we need. It's unlikely that we can make flash memory smaller. We have reached the physical limits," Victor Zhirnov, chief scientist at the Semiconductor Research Corporation, says. "We are facing a crisis that's comparable to the oil crisis in the 1970s. By 2050, we're going to need to store 10 to the 30 bits, compared to 10 to the 23 bits in 2016." That amount of storage space is equivalent to each of the world's seven billion people owning almost six trillion -- that's 10 to the 12th power -- iPhone Xs with 256GB storage space.
The race is on to find another medium capable of storing massive amounts of information in as small a space as possible. Zhirnov and other scientists are looking at the human body, looking to DNA. "Nature has nailed it," Luis Ceze, a professor in the Department of Computer Science and Engineering at the University of Washington, says. "DNA is a molecular storage medium that is remarkable. It's incredibly dense, many, many thousands of times denser than the densest technology that we have today. And DNA is remarkably general. Any information you can map in bits you can store in DNA." It's so dense -- able to store a theoretical maximum of 215 petabytes (215 million gigabytes) in a single gram -- that all the data ever produced could be stored in the back of a tractor trailer truck.
Writing DNA can be an energy-efficient process, too. Consider how the human body is constantly writing and rewriting DNA, and does so on a couple thousand calories a day. And all it needs for storage is a cool, dark place, a significant energy savings when compared to server farms that require huge amounts of energy to run and even more energy to cool.
Picture it: tiny specks of inert DNA made from silicon or another material, stored in cool, dark, dry areas, preserved for all time.
Researchers first succeeded in encoding data onto DNA in 2012, when Harvard University geneticists George Church and Sri Kosuri wrote a 52,000-word book on A, C, G, and T base pairs. Their method only produced 1.28 petabytes per gram of DNA, however, a volume exceeded the next year when a group encoded all 154 Shakespeare sonnets and a 26-second clip of Martin Luther King's "I Have A Dream" speech. In 2017, Columbia University researchers Yaniv Erlich and Dina Zielinski made the process 60 percent more efficient.
The limiting factor today is cost. Erlich said the work his team did cost $7,000 to encode and decode two megabytes of data. To become useful in a widespread way, the price per megabyte needs to plummet. Even advocates concede this point. "Of course it is expensive," Zhirnov says. "But look how much magnetic storage cost in the 1980s. What you store today in your iPhone for virtually nothing would cost many millions of dollars in 1982." There's reason to think the price will continue to fall. Genome readers are improving, getting cheaper, faster, and smaller, and genome sequencing becomes cheaper every year, too. Picture it: tiny specks of inert DNA made from silicon or another material, stored in cool, dark, dry areas, preserved for all time.
"It just takes a few minutes to double a sample. A few more minutes, you double it again. Very quickly, you have thousands or millions of new copies."
Plus, DNA has another advantage over more traditional forms of storage: It's very easy to reproduce. "If you want a second copy of a hard disk drive, you need components for a disk drive, hook both drives up to a computer, and copy. That's a pain," Nick Goldman, a researcher at the European Bioinformatics Institute, says. "DNA, once you have that first sample, it's a process that is absolutely routine in thousands of laboratories around the world to multiply that using polymerase chain reaction [which uses temperature changes or other processes]. It just takes a few minutes to double a sample. A few more minutes, you double it again. Very quickly, you have thousands or millions of new copies."
This ability to duplicate quickly and easily is a positive trait. But, of course, there's also the potential for danger. Does encoding on DNA, the very basis for life, present ethical issues? Could it get out of control and fundamentally alter life as we know it?
The chance is there, but it's remote. The first reason is that storage could be done with only two base pairs, which would serve as replacements for the 0 and 1 digits that make up all digital data. While doing so would decrease the possible density of the storage, it would virtually eliminate the risk that the sequences would be compatible with life.
But even if scientists and researchers choose to use four base pairs, other safeguards are in place that will prevent trouble. According to Ceze, the computer science professor, the snippets of DNA that they write are very short, around 150 nucleotides. This includes the title, the information that's being encoded, and tags to help organize where the snippet should fall in the larger sequence. Furthermore, they generally avoid repeated letters, which dramatically reduces the chance that a protein could be synthesized from the snippet.
"In the future, we'll know enough about someone from a sample of their DNA that we could make a specific poison. That's the danger, not those of us who want to encode DNA for storage."
Inevitably, some DNA will get spilt. "But it's so unlikely that anything that gets created for storage would have a biological interpretation that could interfere with the mechanisms going on in a living organism that it doesn't worry me in the slightest," Goldman says. "We're not of concern for the people who are worried about the ethical issues of synthetic DNA. They are much more concerned about people deliberately engineering anthrax. In the future, we'll know enough about someone from a sample of their DNA that we could make a specific poison. That's the danger, not those of us who want to encode DNA for storage."
In the end, the reality of and risks surrounding encoding on DNA are the same as any scientific advancement: It's another system that is vulnerable to people with bad intentions but not one that is inherently unethical.
"Every human action has some ethical implications," Zhirnov says. "I can use a hammer to build a house or I can use it to harm another person. I don't see why DNA is in any way more or less ethical."
If that house can store all the knowledge in human history, it's worth learning how to build it.
Editor's Note: In response to readers' comments that silicon is one of the earth's most abundant materials, we reached back out to our source, Dr. Victor Zhirnov. He stands by his statement about a coming shortage of silicon, citing this research. The silicon oxide found in beach sand is unsuitable for semiconductors, he says, because the cost of purifying it would be prohibitive. For use in circuit-making, silicon must be refined to a purity of 99.9999999 percent. So the process begins by mining for pure quartz, which can only be found in relatively few places around the world.