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.
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.
There is a lack of political will and leadership on the issue, and the idea that we should seek to do something about aging is generally met with a great deal of suspicion and trepidation. In a large representative study conducted by the Pew Research Center in 2013, only 38% of the respondents said that they would want a treatment that could slow the aging process and allow them to live at least 120 years. Apparently, most people prefer, or at least do not mind, to age and die within a natural lifespan. This result has been confirmed by smaller studies and it is, I think, surprising. Are we not supposed to live in a youth-culture? Are people not supposed to want to stay young and alive forever? Is self-preservation not the strong drive we have always assumed it to be?
We are inundated and saturated with an ideology of death-acceptance.
In my book, The Case against Death, I suggest that we have been culturally conditioned to think that it is virtuous to accept aging and death. We are taught to believe that although aging and death seem gruesome, they are what is best for us, all things considered. This is what we are supposed to think, and the majority accept it. I call this the Wise View because death acceptance has been the dominant view of philosophers since the beginning. Socrates compared our earthly life to an illness and a prison and described death as a healer and a liberator. The Buddha taught that life is suffering and that the way to escape suffering is to end the cycle of birth, death and rebirth. Stoic philosophers from Zeno to Marcus Aurelius believed that everything that happens in accordance with nature is good, and that therefore we should not only accept death but welcome it as an aspect of a perfect totality.
Epicureans agreed with these rival schools and famously argued that death cannot harm us because where we are, death is not, and where death is we are not. We cannot be harmed if we are not, so death is harmless. The simple view that death actually can harm us greatly is one of the least philosophical views one can hold.
In The Case Against Death, philosopher Ingemar Patrick Linden argues that we frown on using science to prolong healthy life only because we're culturally conditioned to think that way.
Many of the stories we tell promote the Wise View. One of the earliest known pieces of literature, the Epic of Gilgamesh, follows Gilgamesh on a quest for eternal life ending with the wisdom that death is the destiny of man. Today we learn about the tedium of immortality from the children’s book Tuck Everlasting by Natalie Babbitt, and we are warned about the vice of wanting to resist death in other books and films such as J.K Rowling’s Harry Potter, where Voldemort must kill Harry as a step towards his own immortality; C.S. Lewis’ The Chronicles of Narnia where the White Witch has gained immortal youth and madness in equal measures; J.R.R. Tolkien’s Lord of the Rings trilogy where the ring extends the wearer’s life but can also destroy them, as exemplified by the creep Gollum; and Doctor Strange where life extension is the one magical power that is taboo. In Star Wars, Yoda, a stereotype of the sage, teaches us the wisdom handed down by philosophers and prophets: “Death is a natural part of life. Rejoice for those around you who transform into the Force. Mourn them do not. Miss them do not.”
We are inundated and saturated with an ideology of death-acceptance. Can the dear reader name one single story where the hero is pursuing anti-aging, longevity or immortality and the villain tries to stop her?
The Wise View resonates with us partly because we think that there is nothing we can do about aging and death, so we do not want to wish for what we cannot have. Youth and immortality are sour grapes to us. Believing that death is, all things considered, not such a bad thing, protects us from experiencing our aging and approaching death as a gruesome tragedy. This need to escape the thought that we are heading towards a personal catastrophe explains why many are so quick to accept arguments against radical life extension, despite their often glaring weaknesses.
One of the most common objections to radical life extension is that aging and death are natural. The problem with this argument is that many things that are natural are very bad, such as cancer, and other things that are not natural are very good, such as a cure for cancer. Why are we so sure that cancer is bad? Because we assume that it is bad to die. Indeed, nothing is more natural than wanting to live. We seem to need philosophers and story tellers to talk us out of it and, in the words of a distinguished bioethicist, “instruct and somewhat moderate our lust for life.”
Another standard objection is that we need a deadline, and that without death we could postpone every action forever. “Death brings urgency and seriousness to life,” say proponents of this view, but there are several problems with this argument. Even if our lives were endless, there would still be many things we would have to do at a certain time, and that could not be redone, for example, saving our planet from being destroyed, or becoming the first person on Venus. And if we prefer pleasant endless lives over unpleasant endless ones, we will have to exercise, eat right, keep our word, develop our talents, show up for time at work, pay our taxes by the due date, remember birthdays, and so on.
The Wise View provides us with a feel-good bromide for the anxiety created by the foreknowledge of our decay and death by telling us that these are not evils, but blessings in disguise. Once perhaps an innocuous delusion, today the view stands in the way of a necessary societal commitment to research that can prolong our healthy life.
Besides, even if we succeeded in ending aging, we would still die from other causes. Given the rate of accidental deaths we would be fortunate to live to age 2000 all things equal. So even if, contrary to what I have argued, we do need a deadline, we can still argue that the natural lifespan that we now labor under is inhuman and that it forces each human to limit her ambitions and to become only a fragment of all that she that could have been. Our tight time constraint imposes tragic choices and inflated opportunity costs. Death does not make life matter; it makes time matter.
The perhaps most awful argument against radical life extension is grounded in a pessimism that holds life in such little regard that it says that best of all is never to have born. This view was expressed by Ecclesiastes in the Hebrew Bible, by Sophocles and several other ancient Greeks, by the German philosopher Arthur Schopenhauer, and recently by, among others, the South African philosopher David Benatar who argues that it is wrong to bring children into the world and that we should euthanize all sentient life. Pessimism, one suspects, largely appeals to some for reasons having to do with personal temperament, but insofar as it is built on factual beliefs, they can be addressed by providing a less negatively biased understanding of the world, by pointing out that curing aging would decrease the badness that they are so hypersensitive to, and by reminding them that if life really becomes unbearable, they are free to quit at any time. Other means of persuasion could include recommending sleep, exercise and taking long brisk walks in nature.
The Wise View provides us with a feel-good bromide for the anxiety created by the foreknowledge of our decay and death by telling us that these are not evils, but blessings in disguise. Once perhaps an innocuous delusion, today the view stands in the way of a necessary societal commitment to research that can prolong our healthy life. We need abandon it and openly admit that aging is a scourge that deserves to be fought with the combined energies equaling those expended on fighting COVID-19, Alzheimer’s disease, cancer, stroke and all the other illnesses for which aging is the greatest risk factor. The fight to end aging transcends ordinary political boundaries and is therefore the kind of grand unifying enterprise that could re-energize a society suffering from divisiveness and the sense of a lack of a common purpose. It is hard to imagine a more worthwhile cause.
Artificial Intelligence is already helping to grow some of the food we eat.
The chef-farmers choose from among 45 types of herb and leafy-greens seeds, plop them into grow trays, and a few weeks later they pick and serve. While success is predicated on at least a small amount of these humans’ care, the systems are autonomously surveilled round-the-clock from Babylon’s base of operations. And artificial intelligence is helping to run the show.
Babylon piloted the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off.
Imagine consistently perfect greens and tomatoes and strawberries, grown hyper-locally, using less water, without chemicals or environmental contaminants. This is the hefty promise of controlled environment agriculture (CEA) — basically, indoor farms that can be hydroponic, aeroponic (plant roots are suspended and fed through misting), or aquaponic (where fish play a role in fertilizing vegetables). But whether they grow 4,160 leafy-green servings per year, like one Babylon farm, or millions of servings, like some of the large, centralized facilities starting to supply supermarkets across the U.S., they seek to minimize failure as much as possible.
Babylon’s soilless hydroponic growing system
Courtesy Babylon Micro-Farms
Here, AI is starting to play a pivotal role. CEA growers use it to help “make sense of what’s happening” to the plants in their care, says Scott Lowman, vice president of applied research at the Institute for Advanced Learning and Research (IALR) in Virginia, a state that’s investing heavily in CEA companies. And although these companies say they’re not aiming for a future with zero human employees, AI is certainly poised to take a lot of human farming intervention out of the equation — for better and worse.
Most of these companies are compiling their own data sets to identify anything that might block the success of their systems. Babylon had already integrated sensor data into its farms to measure heat and humidity, the nutrient content of water, and the amount of light plants receive. Last year, they got a National Science Foundation grant that allowed them to pilot the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off. “Will this plant be healthy tomorrow? Are there things…that the human eye can't see that the plant starts expressing?” says Amandeep Ratte, the company’s head of data science. “If our system can say, Hey, this plant is unhealthy, we can reach out to [users] preemptively about what they’re doing wrong, or is there a disease at the farm?” Ratte says. The earlier the better, to avoid crop failures.
Natural light accounts for 70 percent of Greenswell Growers’ energy use on a sunny day.
Courtesy Greenswell Growers
IALR’s Lowman says that other CEA companies are developing their AI systems to account for the different crops they grow — lettuces come in all shapes and sizes, after all, and each has different growing needs than, for example, tomatoes. The ways they run their operations differs also. Babylon is unusual in its decentralized structure. But centralized growing systems with one main location have variabilities, too. AeroFarms, which recently declared bankruptcy but will continue to run its 140,000-square foot vertical operation in Danville, Virginia, is entirely enclosed and reliant on the intense violet glow of grow lights to produce microgreens.
Different companies have different data needs. What data is essential to AeroFarms isn’t quite the same as for Greenswell Growers located in Goochland County, Virginia. Raising four kinds of lettuce in a 77,000-square-foot automated hydroponic greenhouse, the vagaries of naturally available light, which accounts for 70 percent of Greenswell’s energy use on a sunny day, affect operations. Their tech needs to account for “outside weather impacts,” says president Carl Gupton. “What adjustments do we have to make inside of the greenhouse to offset what's going on outside environmentally, to give that plant optimal conditions? When it's 85 percent humidity outside, the system needs to do X, Y and Z to get the conditions that we want inside.”
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen.
Nevertheless, every CEA system has the same core needs — consistent yield of high quality crops to keep up year-round supply to customers. Additionally, “Everybody’s got the same set of problems,” Gupton says. Pests may come into a facility with seeds. A disease called pythium, one of the most common in CEA, can damage plant roots. “Then you have root disease pressures that can also come internally — a change in [growing] substrate can change the way the plant performs,” Gupton says.
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen. So, while companies amass their own hyper-specific data sets, Lowman foresees a time within the next decade “when there will be some type of [open-source] database that has the most common types of plant stress identified” that growers will be able to tap into. Such databases will “create a community and move the science forward,” says Lowman.
In fact, IALR is working on assembling images for just such a database now. On so-called “smart tables” inside an Institute lab, a team is growing greens and subjects them to various stressors. Then, they’re administering treatments while taking images of every plant every 15 minutes, says Lowman. Some experiments generate 80,000 images; the challenge lies in analyzing and annotating the vast trove of them, marking each one to reflect outcome—for example increasing the phosphate delivery and the plant’s response to it. Eventually, they’ll be fed into AI systems to help them learn.
For all the enthusiasm surrounding this technology, it’s not without downsides. Training just one AI system can emit over 250,000 pounds of carbon dioxide, according to MIT Technology Review. AI could also be used “to enhance environmental benefit for CEA and optimize [its] energy consumption,” says Rozita Dara, a computer science professor at the University of Guelph in Canada, specializing in AI and data governance, “but we first need to collect data to measure [it].”
The chef-farmers can choose from 45 types of herb and leafy-greens seeds.
Courtesy Babylon Micro-Farms
Any system connected to the Internet of Things is also vulnerable to hacking; if CEA grows to the point where “there are many of these similar farms, and you're depending on feeding a population based on those, it would be quite scary,” Dara says. And there are privacy concerns, too, in systems where imaging is happening constantly. It’s partly for this reason, says Babylon’s Ratte, that the company’s in-farm cameras all “face down into the trays, so the only thing [visible] is pictures of plants.”
Tweaks to improve AI for CEA are happening all the time. Greenswell made its first harvest in 2022 and now has annual data points they can use to start making more intelligent choices about how to feed, water, and supply light to plants, says Gupton. Ratte says he’s confident Babylon’s system can already “get our customers reliable harvests. But in terms of how far we have to go, it's a different problem,” he says. For example, if AI could detect whether the farm is mostly empty—meaning the farm’s user hasn’t planted a new crop of greens—it can alert Babylon to check “what's going on with engagement with this user?” Ratte says. “Do they need more training? Did the main person responsible for the farm quit?”
Lowman says more automation is coming, offering greater ability for systems to identify problems and mitigate them on the spot. “We still have to develop datasets that are specific, so you can have a very clear control plan, [because] artificial intelligence is only as smart as what we tell it, and in plant science, there's so much variation,” he says. He believes AI’s next level will be “looking at those first early days of plant growth: when the seed germinates, how fast it germinates, what it looks like when it germinates.” Imaging all that and pairing it with AI, “can be a really powerful tool, for sure.”
Researchers from the University of Cambridge have laid the foundations for growing synthetic embryos that could develop a beating heart, gut and brain.
The organoid revolution
In 1981, scientists discovered how to keep stem cells alive. This was a significant breakthrough, as stem cells have notoriously rigorous demands. Nevertheless, stem cells remained a relatively niche research area, mainly because scientists didn’t know how to convince the cells to turn into other cells.
Then, in 1987, scientists embedded isolated stem cells in a gelatinous protein mixture called Matrigel, which simulated the three-dimensional environment of animal tissue. The cells thrived, but they also did something remarkable: they created breast tissue capable of producing milk proteins. This was the first organoid — a clump of cells that behave and function like a real organ. The organoid revolution had begun, and it all started with a boob in Jello.
For the next 20 years, it was rare to find a scientist who identified as an “organoid researcher,” but there were many “stem cell researchers” who wanted to figure out how to turn stem cells into other cells. Eventually, they discovered the signals (called growth factors) that stem cells require to differentiate into other types of cells.
For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells.
By the end of the 2000s, researchers began combining stem cells, Matrigel, and the newly characterized growth factors to create dozens of organoids, from liver organoids capable of producing the bile salts necessary for digesting fat to brain organoids with components that resemble eyes, the spinal cord, and arguably, the beginnings of sentience.
Synthetic embryos
Organoids possess an intrinsic flaw: they are organ-like. They share some characteristics with real organs, making them powerful tools for research. However, no one has found a way to create an organoid with all the characteristics and functions of a real organ. But Magdalena Żernicka-Goetz, a developmental biologist, might have set the foundation for that discovery.
Żernicka-Goetz hypothesized that organoids fail to develop into fully functional organs because organs develop as a collective. Organoid research often uses embryonic stem cells, which are the cells from which the developing organism is created. However, there are two other types of stem cells in an early embryo: stem cells that become the placenta and those that become the yolk sac (where the embryo grows and gets its nutrients in early development). For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells. In other words, Żernicka-Goetz suspected the best way to grow a functional organoid was to produce a synthetic embryoid.
As described in the aforementioned Nature paper, Żernicka-Goetz and her team mimicked the embryonic environment by mixing these three types of stem cells from mice. Amazingly, the stem cells self-organized into structures and progressed through the successive developmental stages until they had beating hearts and the foundations of the brain.
“Our mouse embryo model not only develops a brain, but also a beating heart [and] all the components that go on to make up the body,” said Żernicka-Goetz. “It’s just unbelievable that we’ve got this far. This has been the dream of our community for years and major focus of our work for a decade and finally we’ve done it.”
If the methods developed by Żernicka-Goetz’s team are successful with human stem cells, scientists someday could use them to guide the development of synthetic organs for patients awaiting transplants. It also opens the door to studying how embryos develop during pregnancy.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
