Technology’s Role in Feeding a Soaring Population Raises This Dilemma
When farmer Terry Wanzek walks out in his fields, he sometimes sees a grove of trees, which reminds him of his grandfather, who planted those trees. Or he looks out over the pond, which deer, ducks and pheasant use for water, and he knows that his grandfather made a decision to drain land and put the pond in that exact spot.
Growing more with fewer resources is becoming increasingly urgent as the Earth's population is expected to hit 9.1 billion by 2050.
"There is a connection that goes beyond running a business and making a profit," says Wanzek, a fourth-generation North Dakota farmer who raises spring wheat, corn, soybeans, barley, dry edible beans and sunflowers. "There is a connection to family, to your ancestors and there is a connection to your posterity and your kids."
Wanzek's corn and soybeans are genetically modified (GM) crops, which means that they have been altered at the DNA level to create desirable traits. This intervention, he says, allows him to start growing earlier and to produce more food per acre.
Growing more with fewer resources is becoming increasingly urgent as the Earth's population is expected to hit 9.1 billion by 2050, with nearly all of the rise coming from developing countries, according to the Food and Agriculture Organization of the United Nations. This population will be urban, which means they'll likely be eating fewer grains and other staple crops, and more vegetables, fruits, meat, dairy, and fish.
Whether those foods will be touched in some way by technology remains a high-stakes question. As for GM foods, the American public is somewhat skeptical: in a recent survey, about one-third of Americans report that they are actively avoiding GMOs or seek out non-GMO labels when shopping and purchasing foods. These consumers fear unsafe food and don't want biotechnologists to tamper with nature. This disconnect—between those who consume food and those who produce it—is only set to intensify as major agricultural companies work to develop further high-tech farming solutions to meet the needs of the growing population.
"I don't think we have a choice going forward. The world isn't getting smaller. We have to come up with a means of using less."
In the future, it may be possible to feed the world. But what if the world doesn't want the food?
A Short History
Genetically modified food is not new. The first such plant (the Flavr Savr tomato) was approved for human consumption and brought to market in 1994, but people didn't like the taste. Today, nine genetically modified food crops are commercially available in the United States (corn, soybean, squash, papaya, alfalfa, sugar beets, canola, potato and apples). Most were modified to increase resistance to disease or pests, or tolerance to a specific herbicide. Such crops have in fact been found to increase yields, with a recent study showing grain yield was up to 24.5 percent higher in genetically engineered corn.
Despite some consumer skepticism, many farmers don't have a problem with GM crops, says Jennie Schmidt, a farmer and registered dietician in Maryland. She says with a laugh that her farm is a "grocery store farm - we grow the ingredients you buy in products at the grocery store." Schmidt's father-in-law, who started the farm, watched the adoption of hybrid corn improve seeds in the 1930s and 1940s.
"It wasn't a difficult leap to see how well these hybrid corn seeds have done over the decades," she says. "So when the GMOs came out, it was a quicker adoption curve, because as farmers they had already been exposed to the first generation and this was just the next step."
Schmidt, for one, is excited about the gene-editing tool CRISPR and other ways biotechnologists can create food like apples or potatoes with a particular enzyme turned off so they don't go brown during oxidation. Other foods in the pipeline include disease-resistant citrus, low-gluten wheat, fungus-resistant bananas, and anti-browning mushrooms.
"We need to not judge our agriculture by yield per acre but nutrition per acre."
"I don't think we have a choice going forward," says Schmidt. "The world isn't getting smaller. We have to come up with a means of using less."
A Different Way Forward?
But others remain convinced that there are better ways to feed the planet. Andrew Kimball, executive director of the Center for Food Safety, a non-profit that promotes organic and sustainable agriculture, says the public has been sold a lie with biotech. "GMO technology is not proven as a food producer," he says. "It's just not being done anywhere at a large scale. Ninety-nine percent of GMOs are corn and soy, and they allow chemical companies to sell more chemicals. But that doesn't increase food or decrease hunger." Instead, Kimball advocates for a pivot from commodity agriculture to farms with crop diversity and animals.
Kimball also suggests a way to use land more appropriately: stop growing so much biofuel. Right now, in the U.S., more than 55 percent of our crop farmland is in corn and soy. About 40 percent of that goes into cars through ethanol, 40 percent is fed to animals and a good bit of the rest goes into high-fructose corn syrup. That leaves only a small amount to feed people, says Kimball. "If you want to feed the world, not just the U.S., you want to make sure to use that land to feed people," he says. "We need to not judge our agriculture by yield per acre but nutrition per acre."
Robert Streiffer, a bioethicist at the University of Wisconsin at Madison, agrees that GMOs haven't really helped alleviate hunger. Glyphosate resistance, one of the traits that is most commonly used in genetically engineered crops, doesn't improve yield or allow crops to be grown in areas where they weren't able to be grown before. "Insect resistance through the insertion of a Bt gene can improve yield, but is mostly used for cotton (which is not a food crop) and corn which goes to feed cattle, a very inefficient method of feeding the hungry, to say the least," he says. Important research is being done in crops such as cassava, which could help relieve global hunger. But in his opinion, these researchers lack the profit potential needed to motivate large private funding sources, so they require more public-sector funding.
"A substantial portion of public opposition is as much about the lack of any perceived benefits for the consumers as it is for outright fear of health or environmental dangers."
"Public opposition to biotech foods is certainly a factor, but I expect this will slowly decline as labels indicating the presence of GE (genetically engineered) ingredients become more common, and as we continue to amass reassuring data on the comparative environmental safety of GE crops," says Streiffer. "A substantial portion of public opposition is as much about the lack of any perceived benefits for the consumers as it is for outright fear of health or environmental dangers."
One sign that the public may be willing to embrace some non-natural foods is the recent interest in cultured meat, which is grown in a lab from animal cells but doesn't require raising or killing animals. A study published last year in PLOS One found that 65 percent of 673 surveyed U.S. individuals would probably or definitely try cultured meat, while only 8.5 percent said they definitely would not. In the future, lab-grown food may become another way to create more food with fewer resources.
Danielle Nierenberg, president of the Food Tank, a nonprofit organization focused on building a global community of safe and healthy food, points to an even more immediate problem: food waste. Globally, about a third of food is thrown out or goes bad before it has a chance to be eaten. She says simply fixing roads and infrastructure in developing countries would go a long way toward ensuring that food reaches the hungry. Focusing on helping small farmers (who grow 70 percent of food around the globe), especially female farmers, would go a long way, she says.
Innovation on the Farm
In addition to good roads, those farmers need fertilizer. Nitrogen-based fertilizers may get a boost in the future from technologies that release nutrients slowly over time, like slow-release medicines based on nanotechnology. In field trials on rice in Sri Lanka, one such nanotech fertilizer increased crop yields by 10 percent, even though it delivered only half the amount of urea compared with traditional fertilizer, according to a study last year.
"I'm not afraid of the food I grow. We live in the same environment, and I feel completely safe."
One startup, the San-Francisco-based Biome Makers, is profiling microbial DNA to give farmers an idea of what their soil needs to better support crops. Joyn Bio, another new startup based in Boston and West Sacramento, is looking to engineer microbes that could reduce farming's reliance on nitrogen fertilizer, which is expensive and harms the environment. (Full disclosure: Joyn Bio and this magazine are funded by the same company, Leaps by Bayer, though leapsmag is editorially independent. Also, Bayer recently acquired Monsanto, the leading producer of genetically engineered seeds and the herbicide Roundup.)
Terry Wanzek, the farmer in North Dakota, says he'd be willing to try any new technology as long as it helps his bottom line – and increases sustainability. "I'm not afraid of the food I grow," he says of his genetically modified produce. "We eat the same food, we live in the same environment, and I feel completely safe."
Only time will tell if people several decades from now feel the same way. But no matter how their food is produced, one thing is certain: those people will need to eat.
Podcast: The Friday Five weekly roundup in health research
The Friday Five covers five stories in health research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Covered in this week's Friday Five:
- Sex differences in cancer
- Promising research on a vaccine for Lyme disease
- Using a super material for brain-like devices
- Measuring your immunity to Covid
- Reducing dementia risk with leisure activities
One day in recent past, scientists at Columbia University’s Creative Machines Lab set up a robotic arm inside a circle of five streaming video cameras and let the robot watch itself move, turn and twist. For about three hours the robot did exactly that—it looked at itself this way and that, like toddlers exploring themselves in a room full of mirrors. By the time the robot stopped, its internal neural network finished learning the relationship between the robot’s motor actions and the volume it occupied in its environment. In other words, the robot built a spatial self-awareness, just like humans do. “We trained its deep neural network to understand how it moved in space,” says Boyuan Chen, one of the scientists who worked on it.
For decades robots have been doing helpful tasks that are too hard, too dangerous, or physically impossible for humans to carry out themselves. Robots are ultimately superior to humans in complex calculations, following rules to a tee and repeating the same steps perfectly. But even the biggest successes for human-robot collaborations—those in manufacturing and automotive industries—still require separating the two for safety reasons. Hardwired for a limited set of tasks, industrial robots don't have the intelligence to know where their robo-parts are in space, how fast they’re moving and when they can endanger a human.
Over the past decade or so, humans have begun to expect more from robots. Engineers have been building smarter versions that can avoid obstacles, follow voice commands, respond to human speech and make simple decisions. Some of them proved invaluable in many natural and man-made disasters like earthquakes, forest fires, nuclear accidents and chemical spills. These disaster recovery robots helped clean up dangerous chemicals, looked for survivors in crumbled buildings, and ventured into radioactive areas to assess damage.
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.”
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.