How We Can Return to Normal Life in the COVID-19 Era
I was asked recently when life might return to normal. The question is simple but the answer is complex, with many knowns, lots of known unknowns, and some unknown unknowns. But I'll give it my best shot.
To get the fatality rate down to flu-like levels would require that we cut Covid-19 fatalities down by a factor of 5.
Since I'm human (and thus want my life back), I might be biased toward optimism.
Here's one way to think about it: Is there another infection that causes sickness and death at levels that we tolerate? The answer, of course, is 'yes': influenza.
According to the Centers for Disease Control, from 2010 to 2019, an average of 30 million Americans had the flu each year, leading to an annual average of 37,000 deaths. This works out to an infection-fatality rate, or IFR, of 0.12 percent. We've tolerated that level of illness death from influenza for a century.
Before going on, let's get one thing out of the way: Back in March, Covid-19 wasn't, as some maintained, "like the flu," and it still isn't. Since then, the U.S. has had 3.9 million confirmed Covid-19 cases and 140,000 deaths, for an IFR of 3.6 percent. Taking all the cases — including asymptomatic patients and those with minimal symptoms who were never tested for Covid-19 — into account, the real IFR is probably 0.6 percent, or roughly 5 times that of the flu.
Nonetheless, even a partly effective vaccine, combined with moderately effective medications, could bring Covid-19 numbers down to a tolerable, flu-like, threshold. It's a goal that seems within our reach.
Chronic mask-wearing and physical distancing are not my idea of normal, nor, I would venture to guess, would most other Americans consider these desirable states in which to live. We need both now to achieve some semblance of normalcy, but they're decidedly not normal life. My notion of normal: daily life with no or minimal mask wearing, open restaurants and bars, ballparks with fans, and theaters with audiences.
My projection for when we might get there: perhaps a year from now.
To get the fatality rate down to flu-like levels would require that we cut Covid-19 fatalities down by a factor of 5, via some combination of fewer symptomatic cases and a lower chance that a symptomatic patient will go on to die. How might that happen?
First, we have to make some impact on young people – getting them to follow the public health directives at higher rates than they are currently. The main reason we need to push younger people to stay safe is that they can spread Covid-19 to vulnerable people (those who are older, with underlying health problems). But, once the most vulnerable are protected (through the deployment of some combination of effective medications and a vaccine), the fact that some young people aren't acting safely – or maybe won't take a vaccine themselves – wouldn't cause so much concern. The key is whether the people at highest risk for bad outcomes are protected.
Then there's the vaccine. The first principle: We don't need a 100 percent-effective vaccine injected into 320 million deltoid muscles (in the U.S. alone). Thank God, since it's fanciful to believe that we can have a vaccine that's 100 percent effective, universally available by next summer, and that each and every American agrees to be vaccinated.
How are we doing in our vaccine journey? We've been having some banner days lately, with recent optimistic reports from several of the vaccine companies. In one report, the leading candidate vaccine, the one effort being led by Oxford University, led to both antibodies and a cellular immune response, a very helpful belt-and-suspenders approach that increases the probability of long-lasting immunity. This good news comes on the heels of the positive news regarding the American vaccine being made by Moderna earlier in July.
While every article about vaccines sounds the obligatory cautionary notes, to date we've checked every box on the path to a safe and effective vaccine. We might not get there, but most experts are now predicting an FDA-approvable vaccine (more than 50 percent effective with no show-stopping side effects) by early 2021.
It is true that we don't know how long immunity will last, but that can be a problem to solve later. In this area, time is our friend. If we can get to an effective vaccine that lasts for a year or two, over time we should be able to discover strategies (more vaccine boosters, new and better medications) to address the possibility of waning immunity.
All things considered, I'm going to put my nickel down on the following optimistic scenario: we'll have one, and likely several, vaccines that have been proven to be more than 50 percent effective and safe by January, 2021.
If only that were the finish line.
Once we vaccinate a large fraction of high-risk patients, having a moderate number of unvaccinated people running around won't pose as much threat.
The investments in manufacturing and distribution should pay off, but it's still inconceivable that we'll be able to get vaccines to 300 million people in three to six months. For the 2009 Swine Flu, we managed to vaccinate about 1 in 4 Americans over six months.
So we'll need to prioritize. First in line will likely be the 55 million Americans over 65, and the six to eight million patient-facing healthcare workers. (How to sort priorities among people under 65 with "chronic diseases" will be a toughie.) Vaccinating 80-100 million vulnerable people, plus clinicians, might be achievable by mid-21.
If we can protect vulnerable people with an effective vaccine (with the less vulnerable waiting their turn over a subsequent 6-12 month period), that may be enough to do the trick. (Of course, vulnerable people may also be least likely to develop immunity in response to a vaccine. That could be an Achilles' heel – time will tell.)
Why might that be enough? Once we vaccinate a large fraction of high-risk patients, having a moderate number of unvaccinated people running around won't pose as much threat. Since they're at lower risk, they have a lower chance of getting sick and dying than those who received the vaccine first.
We're likely to have better meds by then, too. Since March, we've discovered two moderately effective medications for Covid-19 — remdesivir and dexamethasone. It seems likely that we'll find others by next summer, perhaps even a treatment that prevents patients from getting ill in the first place. There are many such therapies, ranging from zinc to convalescent plasma, currently being studied.
Moreover, we know that hospitals that are not overrun with Covid-19 have lower mortality rates. If we've gotten a fairly effective vaccine into most high-risk people, the hospitals are unlikely to be overwhelmed – another factor that may help lower the mortality rate to flu-like levels.
All of these factors – vaccination of most vulnerable people, one or two additional effective medications, hospitals and ICU's that aren't overwhelmed – could easily combine to bring the toll of Covid-19 down to something that resembles that of the flu. Then, we should be able to return to normal life.
Whatever the reason, if enough people refuse the vaccine, all bets are off.
What do I worry about? There's the growing anti-vaxxer movement, for one. On top of that, it seems that many Americans worry that a vaccine discovered in record speed won't be safe, or that the FDA approval process will have been corrupted by political influences. Whatever the reason, if enough people refuse the vaccine, all bets are off.
Assuming only high-risk people do get vaccinated, there will still be cases of Covid-19, maybe even mini-outbreaks, well into 2021 and likely 2022. Obviously, that's not ideal, and we should hope for a vaccine that results in the complete eradication of Covid-19. But the point is that, even with flu-like levels of illness and death, we should still be able to achieve "normal."
Hope is not a strategy, as the saying goes. But it is hope, which is more than we've had for a while.
Awash in a fluid finely calibrated to keep it alive, a human eye rests inside a transparent cubic device. This ECaBox, or Eyes in a Care Box, is a one-of-a-kind system built by scientists at Barcelona’s Centre for Genomic Regulation (CRG). Their goal is to preserve human eyes for transplantation and related research.
In recent years, scientists have learned to transplant delicate organs such as the liver, lungs or pancreas, but eyes are another story. Even when preserved at the average transplant temperature of 4 Centigrade, they last for 48 hours max. That's one explanation for why transplanting the whole eye isn’t possible—only the cornea, the dome-shaped, outer layer of the eye, can withstand the procedure. The retina, the layer at the back of the eyeball that turns light into electrical signals, which the brain converts into images, is extremely difficult to transplant because it's packed with nerve tissue and blood vessels.
These challenges also make it tough to research transplantation. “This greatly limits their use for experiments, particularly when it comes to the effectiveness of new drugs and treatments,” said Maria Pia Cosma, a biologist at Barcelona’s Centre for Genomic Regulation (CRG), whose team is working on the ECaBox.
Eye transplants are desperately needed, but they're nowhere in sight. About 12.7 million people worldwide need a corneal transplant, which means that only one in 70 people who require them, get them. The gaps are international. Eye banks in the United Kingdom are around 20 percent below the level needed to supply hospitals, while Indian eye banks, which need at least 250,000 corneas per year, collect only around 45 to 50 thousand donor corneas (and of those 60 to 70 percent are successfully transplanted).
As for retinas, it's impossible currently to put one into the eye of another person. Artificial devices can be implanted to restore the sight of patients suffering from severe retinal diseases, but the number of people around the world with such “bionic eyes” is less than 600, while in America alone 11 million people have some type of retinal disease leading to severe vision loss. Add to this an increasingly aging population, commonly facing various vision impairments, and you have a recipe for heavy burdens on individuals, the economy and society. In the U.S. alone, the total annual economic impact of vision problems was $51.4 billion in 2017.
Even if you try growing tissues in the petri dish route into organoids mimicking the function of the human eye, you will not get the physiological complexity of the structure and metabolism of the real thing, according to Cosma. She is a member of a scientific consortium that includes researchers from major institutions from Spain, the U.K., Portugal, Italy and Israel. The consortium has received about $3.8 million from the European Union to pursue innovative eye research. Her team’s goal is to give hope to at least 2.2 billion people across the world afflicted with a vision impairment and 33 million who go through life with avoidable blindness.
Their method? Resuscitating cadaveric eyes for at least a month.
If we succeed, it will be the first intact human model of the eye capable of exploring and analyzing regenerative processes ex vivo. -- Maria Pia Cosma.
“We proposed to resuscitate eyes, that is to restore the global physiology and function of human explanted tissues,” Cosma said, referring to living tissues extracted from the eye and placed in a medium for culture. Their ECaBox is an ex vivo biological system, in which eyes taken from dead donors are placed in an artificial environment, designed to preserve the eye’s temperature and pH levels, deter blood clots, and remove the metabolic waste and toxins that would otherwise spell their demise.
Scientists work on resuscitating eyes in the lab of Maria Pia Cosma.
Courtesy of Maria Pia Cosma.
“One of the great challenges is the passage of the blood in the capillary branches of the eye, what we call long-term perfusion,” Cosma said. Capillaries are an intricate network of very thin blood vessels that transport blood, nutrients and oxygen to cells in the body’s organs and systems. To maintain the garland-shaped structure of this network, sufficient amounts of oxygen and nutrients must be provided through the eye circulation and microcirculation. “Our ambition is to combine perfusion of the vessels with artificial blood," along with using a synthetic form of vitreous, or the gel-like fluid that lets in light and supports the the eye's round shape, Cosma said.
The scientists use this novel setup with the eye submersed in its medium to keep the organ viable, so they can test retinal function. “If we succeed, we will ensure full functionality of a human organ ex vivo. It will be the first intact human model of the eye capable of exploring and analyzing regenerative processes ex vivo,” Cosma added.
A rapidly developing field of regenerative medicine aims to stimulate the body's natural healing processes and restore or replace damaged tissues and organs. But for people with retinal diseases, regenerative medicine progress has been painfully slow. “Experiments on rodents show progress, but the risks for humans are unacceptable,” Cosma said.
The ECaBox could boost progress with regenerative medicine for people with retinal diseases, which has been painfully slow because human experiments involving their eyes are too risky. “We will test emerging treatments while reducing animal research, and greatly accelerate the discovery and preclinical research phase of new possible treatments for vision loss at significantly reduced costs,” Cosma explained. Much less time and money would be wasted during the drug discovery process. Their work may even make it possible to transplant the entire eyeball for those who need it.
“It is a very exciting project,” said Sanjay Sharma, a professor of ophthalmology and epidemiology at Queen's University, in Kingston, Canada. “The ability to explore and monitor regenerative interventions will increasingly be of importance as we develop therapies that can regenerate ocular tissues, including the retina.”
Seemingly, there's no sacred religious text or a holy book prohibiting the practice of eye donation.
But is the world ready for eye transplants? “People are a bit weird or very emotional about donating their eyes as compared to other organs,” Cosma said. And much can be said about the problem of eye donor shortage. Concerns include disfigurement and healthcare professionals’ fear that the conversation about eye donation will upset the departed person’s relatives because of cultural or religious considerations. As just one example, Sharma noted the paucity of eye donations in his home country, Canada.
Yet, experts like Sharma stress the importance of these donations for both the recipients and their family members. “It allows them some psychological benefit in a very difficult time,” he said. So why are global eye banks suffering? Is it because the eyes are the windows to the soul?
Seemingly, there's no sacred religious text or a holy book prohibiting the practice of eye donation. In fact, most major religions of the world permit and support organ transplantation and donation, and by extension eye donation, because they unequivocally see it as an “act of neighborly love and charity.” In Hinduism, the concept of eye donation aligns with the Hindu principle of daan or selfless giving, where individuals donate their organs or body after death to benefit others and contribute to society. In Islam, eye donation is a form of sadaqah jariyah, a perpetual charity, as it can continue to benefit others even after the donor's death.
Meanwhile, Buddhist masters teach that donating an organ gives another person the chance to live longer and practice dharma, the universal law and order, more meaningfully; they also dismiss misunderstandings of the type “if you donate an eye, you’ll be born without an eye in the next birth.” And Christian teachings emphasize the values of love, compassion, and selflessness, all compatible with organ donation, eye donation notwithstanding; besides, those that will have a house in heaven, will get a whole new body without imperfections and limitations.
The explanation for people’s resistance may lie in what Deepak Sarma, a professor of Indian religions and philosophy at Case Western Reserve University in Cleveland, calls “street interpretation” of religious or spiritual dogmas. Consider the mechanism of karma, which is about the causal relation between previous and current actions. “Maybe some Hindus believe there is karma in the eyes and, if the eye gets transplanted into another person, they will have to have that karmic card from now on,” Sarma said. “Even if there is peculiar karma due to an untimely death–which might be interpreted by some as bad karma–then you have the karma of the recipient, which is tremendously good karma, because they have access to these body parts, a tremendous gift,” Sarma said. The overall accumulation is that of good karma: “It’s a beautiful kind of balance,” Sarma said.
For the Jews, Christians, and Muslims who believe in the physical resurrection of the body that will be made new in an afterlife, the already existing body is sacred since it will be the basis of a new refashioned body in an afterlife.---Omar Sultan Haque.
With that said, Sarma believes it is a fallacy to personify or anthropomorphize the eye, which doesn’t have a soul, and stresses that the karma attaches itself to the soul and not the body parts. But for scholars like Omar Sultan Haque—a psychiatrist and social scientist at Harvard Medical School, investigating questions across global health, anthropology, social psychology, and bioethics—the hierarchy of sacredness of body parts is entrenched in human psychology. You cannot equate the pinky toe with the face, he explained.
“The eyes are the window to the soul,” Haque said. “People have a hierarchy of body parts that are considered more sacred or essential to the self or soul, such as the eyes, face, and brain.” In his view, the techno-utopian transhumanist communities (especially those in Silicon Valley) have reduced the totality of a person to a mere material object, a “wet robot” that knows no sacredness or hierarchy of human body parts. “But for the Jews, Christians, and Muslims who believe in the physical resurrection of the body that will be made new in an afterlife, the [already existing] body is sacred since it will be the basis of a new refashioned body in an afterlife,” Haque said. “You cannot treat the body like any old material artifact, or old chair or ragged cloth, just because materialistic, secular ideologies want so,” he continued.
For Cosma and her peers, however, the very definition of what is alive or not is a bit semantic. “As soon as we die, the electrophysiological activity in the eye stops,” she said. “The goal of the project is to restore this activity as soon as possible before the highly complex tissue of the eye starts degrading.” Cosma’s group doesn’t yet know when they will be able to keep the eyes alive and well in the ECaBox, but the consensus is that the sooner the better. Hopefully, the taboos and fears around the eye donations will dissipate around the same time.
As Our AI Systems Get Better, So Must We
As the power and capability of our AI systems increase by the day, the essential question we now face is what constitutes peak human. If we stay where we are while the AI systems we are unleashing continually get better, they will meet and then exceed our capabilities in an ever-growing number of domains. But while some technology visionaries like Elon Musk call for us to slow down the development of AI systems to buy time, this approach alone will simply not work in our hyper-competitive world, particularly when the potential benefits of AI are so great and our frameworks for global governance are so weak. In order to build the future we want, we must also become ever better humans.
The list of activities we once saw as uniquely human where AIs have now surpassed us is long and growing. First, AI systems could beat our best chess players, then our best Go players, then our best champions of multi-player poker. They can see patterns far better than we can, generate medical and other hypotheses most human specialists miss, predict and map out new cellular structures, and even generate beautiful, and, yes, creative, art.
A recent paper by Microsoft researchers analyzing the significant leap in capabilities in OpenAI’s latest AI bot, ChatGPT-4, asserted that the algorithm can “solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting.” Calling this functionality “strikingly close to human-level performance,” the authors conclude it “could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system.”
The concept of AGI has been around for decades. In its common use, the term suggests a time when individual machines can do many different things at a human level, not just one thing like playing Go or analyzing radiological images. Debating when AGI might arrive, a favorite pastime of computer scientists for years, now has become outdated.
We already have AI algorithms and chatbots that can do lots of different things. Based on the generalist definition, in other words, AGI is essentially already here.
Unfettered by the evolved capacity and storage constraints of our brains, AI algorithms can access nearly all of the digitized cultural inheritance of humanity since the dawn of recorded history and have increasing access to growing pools of digitized biological data from across the spectrum of life.
Once we recognize that both AI systems and humans have unique superpowers, the essential question becomes what each of us can do better than the other and what humans and AIs can best do in active collaboration. The future of our species will depend upon our ability to safely, dynamically, and continually figure that out.
With these ever-larger datasets, rapidly increasing computing and memory power, and new and better algorithms, our AI systems will keep getting better faster than most of us can today imagine. These capabilities have the potential to help us radically improve our healthcare, agriculture, and manufacturing, make our economies more productive and our development more sustainable, and do many important things better.
Soon, they will learn how to write their own code. Like human children, in other words, AI systems will grow up. But even that doesn’t mean our human goose is cooked.
Just like dolphins and dogs, these alternate forms of intelligence will be uniquely theirs, not a lesser or greater version of ours. There are lots of things AI systems can't do and will never be able to do because our AI algorithms, for better and for worse, will never be human. Our embodied human intelligence is its own thing.
Our human intelligence is uniquely ours based on the capacities we have developed in our 3.8-billion-year journey from single cell organisms to us. Our brains and bodies represent continuous adaptations on earlier models, which is why our skeletal systems look like those of lizards and our brains like most other mammals with some extra cerebral cortex mixed in. Human intelligence isn’t just some type of disembodied function but the inextricable manifestation of our evolved physical reality. It includes our sensory analytical skills and all of our animal instincts, intuitions, drives, and perceptions. Disembodied machine intelligence is something different than what we have evolved and possess.
Because of this, some linguists including Noam Chomsky have recently argued that AI systems will never be intelligent as long as they are just manipulating symbols and mathematical tokens without any inherent understanding. Nothing could be further from the truth. Anyone interacting with even first-generation AI chatbots quickly realizes that while these systems are far from perfect or omniscient and can sometimes be stupendously oblivious, they are surprisingly smart and versatile and will get more so… forever. We have little idea even how our own minds work, so judging AI systems based on their output is relatively close to how we evaluate ourselves.
Anyone not awed by the potential of these AI systems is missing the point. AI’s newfound capacities demand that we work urgently to establish norms, standards, and regulations at all levels from local to global to manage the very real risks. Pausing our development of AI systems now doesn’t make sense, however, even if it were possible, because we have no sufficient ways of uniformly enacting such a pause, no plan for how we would use the time, and no common framework for addressing global collective challenges like this.
But if all we feel is a passive awe for these new capabilities, we will also be missing the point.
Human evolution, biology, and cultural history are not just some kind of accidental legacy, disability, or parlor trick, but our inherent superpower. Our ancestors outcompeted rivals for billions of years to make us so well suited to the world we inhabit and helped build. Our social organization at scale has made it possible for us to forge civilizations of immense complexity, engineer biology and novel intelligence, and extend our reach to the stars. Our messy, embodied, intuitive, social human intelligence is roughly mimicable by AI systems but, by definition, never fully replicable by them.
Once we recognize that both AI systems and humans have unique superpowers, the essential question becomes what each of us can do better than the other and what humans and AIs can best do in active collaboration. We still don't know. The future of our species will depend upon our ability to safely, dynamically, and continually figure that out.
As we do, we'll learn that many of our ideas and actions are made up of parts, some of which will prove essentially human and some of which can be better achieved by AI systems. Those in every walk of work and life who most successfully identify the optimal contributions of humans, AIs, and the two together, and who build systems and workflows empowering humans to do human things, machines to do machine things, and humans and machines to work together in ways maximizing the respective strengths of each, will be the champions of the 21st century across all fields.
The dawn of the age of machine intelligence is upon us. It’s a quantum leap equivalent to the domestication of plants and animals, industrialization, electrification, and computing. Each of these revolutions forced us to rethink what it means to be human, how we live, and how we organize ourselves. The AI revolution will happen more suddenly than these earlier transformations but will follow the same general trajectory. Now is the time to aggressively prepare for what is fast heading our way, including by active public engagement, governance, and regulation.
AI systems will not replace us, but, like these earlier technology-driven revolutions, they will force us to become different humans as we co-evolve with our technology. We will never reach peak human in our ongoing evolutionary journey, but we’ve got to manage this transition wisely to build the type of future we’d like to inhabit.
Alongside our ascending AIs, we humans still have a lot of climbing to do.