Aerosol scientists say that the evidence points to airborne transmission of COVID-19 "beyond any reasonable doubt."
The organization's late March messaging, still available on social media, is a digital graphic saying, "FACT CHECK: COVID-19 is NOT Airborne".
Screenshot of WHO's Tweet from March 28, 2020 that is still published.
The petition asks for a course correct: "We, citizens of the world, request that the World Health Organization (WHO) recognize the compelling scientific evidence that SARS-CoV-2 spreads by aerosol transmission ("airborne") and urge the WHO to immediately develop and initiate clear recommendations to enable people to protect themselves."
In the vacuum of the WHO's inaction, aerosol scientists around the world scrambled to raise awareness of what they saw as a grave error.
"Almost immediately after that [March 28] announcement, we formed a group of 239 scientists from many countries and disciplines to convince them that they should acknowledge that there is airborne transmission, but we find that they are totally dead set against it," says Dr. Jose Jimenez, a chemistry professor at the University of Colorado at Boulder who has studied aerosols for 20 years. He supports the citizen petition.
In a letter to the WHO back in July, he and his colleagues wrote: "Studies by the signatories and other scientists have demonstrated beyond any reasonable doubt that viruses are released during exhalation, talking, and coughing in microdroplets small enough to remain aloft in air and pose a risk of exposure at distances beyond 1–2 m from an infected individual."
The scientists have also gone direct to the public with their findings: They published a comprehensive Google doc with detailed answers to many people's frequently asked questions about how to protect themselves, addressing issues ranging from the best masks and air filters to how to deal with passing someone outdoors and much more.
It's worth noting that the CDC has now modified its COVID FAQ to include airborne transmission as a "less common way" for the virus to spread. This update took place after the CDC stated in September that it is "possible" the virus spreads via airborne transmission – only to reverse course and remove the language from its website several days later. The CDC's website now states that some viruses, including SARS-Cov-2, "may be able to infect people who are further than 6 feet away from the person who is infected or after that person has left the space."
Basset Allen notes that after the scientists' open letter, the WHO "added ventilation to public communications about how to prevent infection, but they haven't explained why."
When contacted, a WHO representative had no specific comment and shared its late March announcement as well as its latest guidelines on transmission. In part, its statement says, "Current evidence suggests that the main way the virus spreads is by respiratory droplets among people who are in close contact with each other. Aerosol transmission can occur in specific settings, particularly in indoor, crowded and inadequately ventilated spaces, where infected person(s) spend long periods of time with others, such as restaurants, choir practices, fitness classes, nightclubs, offices and/or places of worship. More studies are underway to better understand the conditions in which aerosol transmission is occurring outside of medical facilities where specific medical procedures, called aerosol-generating procedures, are conducted."
A forceful and clear message acknowledging the evidence could make it easier to standardize school and office ventilation, petitioners argue.
Aerosol scientist Jimenez was dismayed by the WHO's response.
"The first part is an error in my opinion," he says. "Current evidence suggests that the main way the virus spreads is inhalation of aerosols.…WHO is way behind, unfortunately.
"The second part is incomplete," Jimenez continues. "Aerosol transmission can happen in those indoor crowded low-ventilation spaces. But if aerosols can accumulate under those conditions and cause infection, they must be extremely infective in close proximity when talking, since they are much more concentrated there. Just like talking close to a smoker you would inhale much more smoke (which is an aerosol) than if you were in the same room, but let's say 10 or 15 feet away."
He adds, "The WHO and others are making the assumption that if this goes through the air, then everyone who is infected is putting a lot of virus into the air at all times, but we know that's wrong: People are infectious for a short period of time before and during their symptoms. In China, they have measured how much virus comes out of people, and they see that the emission is sporadic: The virus can come out in millions of viral [particles] per hour, but it doesn't happen all the time."
The petition's co-creator, Basset Allen, says that her life experience showed her the best way to make a change. "My involvement with this effort is entirely personal," she says. "I was first introduced to HIV treatment activism as a college student and what I learned about campaigning and power has been relevant in almost every other project I've worked on since then. HIV activism taught me that everyday people can win big, life-saving policy changes if they build expertise and work strategically to push decision makers."
The petition and its advocates argue that the WHO's mixed messaging is causing real harm. For instance, a forceful and clear message acknowledging the evidence could make it easier to standardize school and office ventilation, they argue. Anecdotally, some schools have refused to install HEPA filtration in their classrooms due to a lack of specific guidance from health agencies. (Note: The CDC now recommends improving central air filtration and considering the use of portable HEPA filters in classrooms.)
As the holidays approach, a clear and unified message from all influential health agencies would also help people understand why it is still important to wear masks while physical distancing, especially indoors.
"Personally, I cheered when I heard President-Elect Biden mention ventilation upgrades in schools during the first 10 minutes of his October town hall event, and again in the second debate," Basset Allen says. "Unfortunately, we're still more than two months away from the Biden administration taking over the U.S. COVID-19 response and we have to do absolutely everything we can right now to save as many lives as possible. Increasing awareness of airborne transmission and mitigation strategies can't wait. WHO can use its power to help close that gap, here and around the world."
Giving robots self-awareness as they move through space - and maybe even providing them with gene-like methods for storing rules of behavior - could be important steps toward creating more intelligent machines.
Now roboticists are going a step further, training their creations to do even better: understand their own image in space and interact with humans like humans do. Today, there are already robot-teachers like KeeKo, robot-pets like Moffin, robot-babysitters like iPal, and robotic companions for the elderly like Pepper.
But even these reasonably intelligent creations still have huge limitations, some scientists think. “There are niche applications for the current generations of robots,” says professor Anthony Zador at Cold Spring Harbor Laboratory—but they are not “generalists” who can do varied tasks all on their own, as they mostly lack the abilities to improvise, make decisions based on a multitude of facts or emotions, and adjust to rapidly changing circumstances. “We don’t have general purpose robots that can interact with the world. We’re ages away from that.”
Robotic spatial self-awareness – the achievement by the team at Columbia – is an important step toward creating more intelligent machines. Hod Lipson, professor of mechanical engineering who runs the Columbia lab, says that future robots will need this ability to assist humans better. Knowing how you look and where in space your parts are, decreases the need for human oversight. It also helps the robot to detect and compensate for damage and keep up with its own wear-and-tear. And it allows robots to realize when something is wrong with them or their parts. “We want our robots to learn and continue to grow their minds and bodies on their own,” Chen says. That’s what Zador wants too—and on a much grander level. “I want a robot who can drive my car, take my dog for a walk and have a conversation with me.”
Columbia scientists have trained a robot to become aware of its own "body," so it can map the right path to touch a ball without running into an obstacle, in this case a square.
Jane Nisselson and Yinuo Qin/ Columbia Engineering
Today’s technological advances are making some of these leaps of progress possible. One of them is the so-called Deep Learning—a method that trains artificial intelligence systems to learn and use information similar to how humans do it. Described as a machine learning method based on neural network architectures with multiple layers of processing units, Deep Learning has been used to successfully teach machines to recognize images, understand speech and even write text.
Trained by Google, one of these language machine learning geniuses, BERT, can finish sentences. Another one called GPT3, designed by San Francisco-based company OpenAI, can write little stories. Yet, both of them still make funny mistakes in their linguistic exercises that even a child wouldn’t. According to a paper published by Stanford’s Center for Research on Foundational Models, BERT seems to not understand the word “not.” When asked to fill in the word after “A robin is a __” it correctly answers “bird.” But try inserting the word “not” into that sentence (“A robin is not a __”) and BERT still completes it the same way. Similarly, in one of its stories, GPT3 wrote that if you mix a spoonful of grape juice into your cranberry juice and drink the concoction, you die. It seems that robots, and artificial intelligence systems in general, are still missing some rudimentary facts of life that humans and animals grasp naturally and effortlessly.
How does one give robots a genome? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create.
It's not exactly the robots’ fault. Compared to humans, and all other organisms that have been around for thousands or millions of years, robots are very new. They are missing out on eons of evolutionary data-building. Animals and humans are born with the ability to do certain things because they are pre-wired in them. Flies know how to fly, fish knows how to swim, cats know how to meow, and babies know how to cry. Yet, flies don’t really learn to fly, fish doesn’t learn to swim, cats don’t learn to meow, and babies don’t learn to cry—they are born able to execute such behaviors because they’re preprogrammed to do so. All that happens thanks to the millions of years of evolutions wired into their respective genomes, which give rise to the brain’s neural networks responsible for these behaviors. Robots are the newbies, missing out on that trove of information, Zador argues.
A neuroscience professor who studies how brain circuitry generates various behaviors, Zador has a different approach to developing the robotic mind. Until their creators figure out a way to imbue the bots with that information, robots will remain quite limited in their abilities. Each model will only be able to do certain things it was programmed to do, but it will never go above and beyond its original code. So Zador argues that we have to start giving robots a genome.
How does one do that? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create. Genomes lay out rules for brain development. Specifically, the genome encodes blueprints for wiring up our nervous system—the details of which neurons are connected, the strength of those connections and other specs that will later hold the information learned throughout life. “Our genomes serve as blueprints for building our nervous system and these blueprints give rise to a human brain, which contains about 100 billion neurons,” Zador says.
If you think what a genome is, he explains, it is essentially a very compact and compressed form of information storage. Conceptually, genomes are similar to CliffsNotes and other study guides. When students read these short summaries, they know about what happened in a book, without actually reading that book. And that’s how we should be designing the next generation of robots if we ever want them to act like humans, Zador says. “We should give them a set of behavioral CliffsNotes, which they can then unwrap into brain-like structures.” Robots that have such brain-like structures will acquire a set of basic rules to generate basic behaviors and use them to learn more complex ones.
Currently Zador is in the process of developing algorithms that function like simple rules that generate such behaviors. “My algorithms would write these CliffsNotes, outlining how to solve a particular problem,” he explains. “And then, the neural networks will use these CliffsNotes to figure out which ones are useful and use them in their behaviors.” That’s how all living beings operate. They use the pre-programmed info from their genetics to adapt to their changing environments and learn what’s necessary to survive and thrive in these settings.
For example, a robot’s neural network could draw from CliffsNotes with “genetic” instructions for how to be aware of its own body or learn to adjust its movements. And other, different sets of CliffsNotes may imbue it with the basics of physical safety or the fundamentals of speech.
At the moment, Zador is working on algorithms that are trying to mimic neuronal blueprints for very simple organisms—such as earthworms, which have only 302 neurons and about 7000 synapses compared to the millions we have. That’s how evolution worked, too—expanding the brains from simple creatures to more complex to the Homo Sapiens. But if it took millions of years to arrive at modern humans, how long would it take scientists to forge a robot with human intelligence? That’s a billion-dollar question. Yet, Zador is optimistic. “My hypotheses is that if you can build simple organisms that can interact with the world, then the higher level functions will not be nearly as challenging as they currently are.”
