Cows on a pasture, who, among other mammals, could experience immense suffering from the New World screwworm.
Combining CRISPR genome editing with the natural phenomenon of gene drive allows us to rewrite the genomes of wild organisms. The benefits of saving children from malaria by editing mosquitoes are obvious and much discussed, but humans aren't the only creatures who suffer. If we gain the power to intervene in a natural world "red in tooth and claw," yet decline to use it, are we morally responsible for the animal suffering that we could have prevented?
Given the power to alter the workings of the natural world, are we morally obligated to use it?
The scenario that may redefine our relationship with the natural world begins with fine clothing. You're dressed to the nines for a formal event, but you arrived early, and it's such a beautiful day that you decided to take a stroll by the nearby lake. Suddenly, you hear the sound of splashing and screams. A child is drowning! Will you dive in to save them? Or let them die, and preserve your expensive outfit?
The philosopher Peter Singer posited this scenario to show that we are all terrible human beings. Just about everyone would save the child and ruin the outfit... leading Singer to question why so few of us give equivalent amounts of money to save children on the other side of the world. The Against Malaria Foundation averages one life saved for every $7000.
But despite having a local bias, our moral compasses aren't completely broken. You never even considered letting the child drown because the situation wasn't your fault. That's because the cause of the problem simply isn't relevant: as the one who could intervene, the consequences are on your head. We are morally responsible for intervening in situations we did not create.
There is a critical difference between Singer's original scenario and the one above: in his version, it was a muddy pond. Any adult can rescue a child from a muddy pond, but a lake is different; you can only save the child if you know how to swim. We only become morally responsible when we acquire the power to intervene.
Few would disagree with either of these moral statements, but when they are combined with increasingly powerful technologies, the implications are deeply unsettling. Given the power to alter the workings of the natural world, are we morally obligated to use it? Recent developments suggest we had best determine the answer soon because, technologically, we are learning to swim. What choices will we make?
Gene drive is a natural phenomenon that occurs when a genetic element reliably spreads through a population even though it reduces the reproductive fitness of individual organisms. Nature has evolved many different mechanisms that result in gene drive, so many that it's nearly impossible to find an organism that doesn't have at least one driving element somewhere in its genome. More than half of our own DNA comprises the broken remnants of gene drives, plus a few active copies.
Scientists have long dreamed of harnessing gene drive to block mosquito-borne disease, with little success. Then came CRISPR genome editing, which works by cutting target genes and replacing them with a new sequence. What happens if you replace the original sequence with the edited version and an encoded copy of the CRISPR system? Gene drive.
CRISPR is a molecular scalpel that we can use to cut, and therefore replace, just about any DNA sequence in any cell. Encode the instructions for the CRISPR system adjacent to the new sequence, and genome editing will occur in the reproductive cells of subsequent generations of heterozygotes, always converting the original wild-type version to the new edited version. By ensuring that offspring will all be born of one sex, or by arranging for organisms that inherit two copies of the gene drive to be sterile, it's theoretically possible to cause a population crash.
(Credit: Esvelt)
When my colleagues and I first described this technology in 2014, we initially focused on the imperative for early transparency. Gene drive research is more like civic governance than traditional technology development: you can decline a treatment recommended by your doctor, but you can’t opt out when people change the shared environment. Applying the traditional closeted model of science to gene drive actively denies people a voice in decisions intended to affect them - and reforming scientific incentives for gene drive could be the first step to making all of science faster and safer.
But open gene drive research is clearly aligned with virtually all of our values. It's when technology places our deepest moral beliefs in conflict that we struggle, and learn who we truly are.
Two of our strongest moral beliefs include our reverence for the natural world and our abhorrence of suffering. Yet some natural species inherently cause tremendous suffering. Are we morally obligated to alter or even eradicate them?
To anyone who doubts that the natural world can inflict unimaginable suffering, consider the New World screwworm.
Judging by history, the answer depends on who is doing the suffering. We view the eradication of smallpox as one of our greatest triumphs, clearly demonstrating that we value human lives over the existence of disease-causing microorganisms. The same principle holds today for malaria: few would argue against using gene drive to crash populations of malarial mosquitoes to help eradicate the disease. There are more than 3500 species of mosquitoes, only three of which would be affected, and once malaria is gone, the mosquitoes could be allowed to recover. It would be extremely surprising if African nations decided not to eradicate malaria.
The more interesting question concerns our moral obligations to animals in the state of nature.
To anyone who doubts that the natural world can inflict unimaginable suffering, consider the New World screwworm, Cochyliomyia hominivorax. Female screwworm flies lay their eggs in open wounds, generating maggots that devour healthy tissue, gluttonously burrowing into the flesh of their host until they drop, engorged and sated, to metamorphose. Yet before they fall, the maggots in a wound emit a pheromone attracting new females, thereby acting as both conductors and performers in a macabre parade that consumes the host alive. The pain is utterly excruciating, so much so that infested people often require morphine before doctors can even examine the wound. Worst of all, the New World screwworm specializes in devouring complex mammals.
Every second of every day, hundreds of millions of animals suffer the excruciating agony of being eaten alive. It has been so throughout North and South America for millions of years. Until 2001, when humanity eradicated the last screwworm fly north of Panama using the “sterile insect technique�. This was not done to protect wild animals or even people, but for economic reasons: the cost of the program was small relative to the immense damage wrought by the screwworm on North American cattle, sheep, and goats. There were no obvious ecological effects. Despite being almost completely unknown even among animal rights activists, the screwworm elimination campaign may well have been one of the greatest triumphs of animal well-being.
Unfortunately, sterile insect technique isn't powerful enough to eradicate the screwworm from South America, where it is more entrenched and protected by the rougher terrain. But gene drive is.
Contrary to news hype, gene drive alone can't cause extinction, but if combined with conventional measures it might be possible to remove targeted species from the wild. For certain species that cause immense suffering, we may be morally obligated to do just that.
(Credit: Esvelt)
South Americans may well decide to eradicate screwworm for the same economic reasons that it was eradicated from North America: the fly inflicts $4 billion in annual damages on struggling rural communities that can least afford it. It need not go extinct, of course; the existence of the sterile insect facility in Panama proves that we can maintain the screwworm indefinitely in captivity on already dead meat.
Yet if for some reason humanity chooses to leave the screwworm as it is - even for upstanding moral reasons, whatever those may be - the knowledge of our responsibility should haunt us.
Tennyson wrote,
Are God and Nature then at strife,
That Nature lends such evil dreams?
So careful of the type she seems,
So careless of the single life.
Evolution by natural selection cares nothing for the single life, nor suffering, nor euphoria, save for their utility in replication. Theoretically, we do. But how much?
[Editor's Note: This story was originally published in May 2018. We are resurfacing archive hits while our staff is on vacation.]
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.
