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.
Researchers probe extreme gene therapy for severe alcoholism
Story by Freethink
A single shot — a gene therapy injected into the brain — dramatically reduced alcohol consumption in monkeys that previously drank heavily. If the therapy is safe and effective in people, it might one day be a permanent treatment for alcoholism for people with no other options.
The challenge: Alcohol use disorder (AUD) means a person has trouble controlling their alcohol consumption, even when it is negatively affecting their life, job, or health.
In the U.S., more than 10 percent of people over the age of 12 are estimated to have AUD, and while medications, counseling, or sheer willpower can help some stop drinking, staying sober can be a huge struggle — an estimated 40-60 percent of people relapse at least once.
A team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
According to the CDC, more than 140,000 Americans are dying each year from alcohol-related causes, and the rate of deaths has been rising for years, especially during the pandemic.
The idea: For occasional drinkers, alcohol causes the brain to release more dopamine, a chemical that makes you feel good. Chronic alcohol use, however, causes the brain to produce, and process, less dopamine, and this persistent dopamine deficit has been linked to alcohol relapse.
There is currently no way to reverse the changes in the brain brought about by AUD, but a team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
To find out, they tested it in heavy-drinking monkeys — and the animals’ alcohol consumption dropped by 90% over the course of a year.
How it works: The treatment centers on the protein GDNF (“glial cell line-derived neurotrophic factor”), which supports the survival of certain neurons, including ones linked to dopamine.
For the new study, a harmless virus was used to deliver the gene that codes for GDNF into the brains of four monkeys that, when they had the option, drank heavily — the amount of ethanol-infused water they consumed would be equivalent to a person having nine drinks per day.
“We targeted the cell bodies that produce dopamine with this gene to increase dopamine synthesis, thereby replenishing or restoring what chronic drinking has taken away,” said co-lead researcher Kathleen Grant.
To serve as controls, another four heavy-drinking monkeys underwent the same procedure, but with a saline solution delivered instead of the gene therapy.
The results: All of the monkeys had their access to alcohol removed for two months following the surgery. When it was then reintroduced for four weeks, the heavy drinkers consumed 50 percent less compared to the control group.
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
The researchers then took the alcohol away for another four weeks, before giving it back for four. They repeated this cycle for a year, and by the end of it, the treated monkeys’ consumption had fallen by more than 90 percent compared to the controls.
“Drinking went down to almost zero,” said Grant. “For months on end, these animals would choose to drink water and just avoid drinking alcohol altogether. They decreased their drinking to the point that it was so low we didn’t record a blood-alcohol level.”
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
Looking ahead: Dopamine is involved in a lot more than addiction, so more research is needed to not only see if the results translate to people but whether the gene therapy leads to any unwanted changes to mood or behavior.
Because the therapy requires invasive brain surgery and is likely irreversible, it’s unlikely to ever become a common treatment for alcoholism — but it could one day be the only thing standing between people with severe AUD and death.
“[The treatment] would be most appropriate for people who have already shown that all our normal therapeutic approaches do not work for them,” said Grant. “They are likely to create severe harm or kill themselves or others due to their drinking.”
This article originally appeared on Freethink, home of the brightest minds and biggest ideas of all time.
Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?
The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.
But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.
Generative AI tools are based on large language models (LLMs), with most well-known being various versions of GPT. LLMs can perform natural language processing, including translating, summarizing and answering questions. They use artificial neural networks, called deep learning or machine learning. Inspired by the human brain, neural networks are made of millions of artificial neurons. “The basic principles of neural networks were known even in the 1950s and 1960s,” Toyama says, “but it’s only now, with the tremendous amount of compute power that we have, as well as huge amounts of data, that it’s become possible to train generative AI models.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries.
In recent months, much attention has gone to the transformative benefits of these technologies. But it’s important to consider that these remarkable advances may come at a price.
AI’s carbon footprint
In their latest annual report, 2023 Landscape: Confronting Tech Power, the AI Now Institute, an independent policy research entity focusing on the concentration of power in the tech industry, says: “The constant push for scale in artificial intelligence has led Big Tech firms to develop hugely energy-intensive computational models that optimize for ‘accuracy’—through increasingly large datasets and computationally intensive model training—over more efficient and sustainable alternatives.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries. In 2019, Emma Strubell, then a graduate researcher at the University of Massachusetts Amherst, estimated that training a single LLM resulted in over 280,000 kg in CO2 emissions—an equivalent of driving almost 1.2 million km in a gas-powered car. A couple of years later, David Patterson, a computer scientist from the University of California Berkeley, and colleagues, estimated GPT-3’s carbon footprint at over 550,000 kg of CO2 In 2022, the tech company Hugging Face, estimated the carbon footprint of its own language model, BLOOM, as 25,000 kg in CO2 emissions. (BLOOM’s footprint is lower because Hugging Face uses renewable energy, but it doubled when other life-cycle processes like hardware manufacturing and use were added.)
Luckily, despite the growing size and numbers of data centers, their increasing energy demands and emissions have not kept pace proportionately—thanks to renewable energy sources and energy-efficient hardware.
But emissions don’t tell the full story.
AI’s hidden human cost
“If historical colonialism annexed territories, their resources, and the bodies that worked on them, data colonialism’s power grab is both simpler and deeper: the capture and control of human life itself through appropriating the data that can be extracted from it for profit.” So write Nick Couldry and Ulises Mejias, authors of the book The Costs of Connection.
The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
Technologies we use daily inexorably gather our data. “Human experience, potentially every layer and aspect of it, is becoming the target of profitable extraction,” Couldry and Meijas say. This feeds data capitalism, the economic model built on the extraction and commodification of data. While we are being dispossessed of our data, Big Tech commodifies it for their own benefit. This results in consolidation of power structures that reinforce existing race, gender, class and other inequalities.
“The political economy around tech and tech companies, and the development in advances in AI contribute to massive displacement and pollution, and significantly changes the built environment,” says technologist and activist Yeshi Milner, who founded Data For Black Lives (D4BL) to create measurable change in Black people’s lives using data. The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
AI’s recent explosive growth spiked the demand for manual, behind-the-scenes tasks, creating an industry described by Mary Gray and Siddharth Suri as “ghost work” in their book. This invisible human workforce that lies behind the “magic” of AI, is overworked and underpaid, and very often based in the Global South. For example, workers in Kenya who made less than $2 an hour, were the behind the mechanism that trained ChatGPT to properly talk about violence, hate speech and sexual abuse. And, according to an article in Analytics India Magazine, in some cases these workers may not have been paid at all, a case for wage theft. An exposé by the Washington Post describes “digital sweatshops” in the Philippines, where thousands of workers experience low wages, delays in payment, and wage theft by Remotasks, a platform owned by Scale AI, a $7 billion dollar American startup. Rights groups and labor researchers have flagged Scale AI as one company that flouts basic labor standards for workers abroad.
It is possible to draw a parallel with chattel slavery—the most significant economic event that continues to shape the modern world—to see the business structures that allow for the massive exploitation of people, Milner says. Back then, people got chocolate, sugar, cotton; today, they get generative AI tools. “What’s invisible through distance—because [tech companies] also control what we see—is the massive exploitation,” Milner says.
“At Data for Black Lives, we are less concerned with whether AI will become human…[W]e’re more concerned with the growing power of AI to decide who’s human and who’s not,” Milner says. As a decision-making force, AI becomes a “justifying factor for policies, practices, rules that not just reinforce, but are currently turning the clock back generations years on people’s civil and human rights.”
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement.
Nuria Oliver, a computer scientist, and co-founder and vice-president of the European Laboratory of Learning and Intelligent Systems (ELLIS), says that instead of focusing on the hypothetical existential risks of today’s AI, we should talk about its real, tangible risks.
“Because AI is a transverse discipline that you can apply to any field [from education, journalism, medicine, to transportation and energy], it has a transformative power…and an exponential impact,” she says.
AI's accountability
“At the core of what we were arguing about data capitalism [is] a call to action to abolish Big Data,” says Milner. “Not to abolish data itself, but the power structures that concentrate [its] power in the hands of very few actors.”
A comprehensive AI Act currently negotiated in the European Parliament aims to rein Big Tech in. It plans to introduce a rating of AI tools based on the harms caused to humans, while being as technology-neutral as possible. That sets standards for safe, transparent, traceable, non-discriminatory, and environmentally friendly AI systems, overseen by people, not automation. The regulations also ask for transparency in the content used to train generative AIs, particularly with copyrighted data, and also disclosing that the content is AI-generated. “This European regulation is setting the example for other regions and countries in the world,” Oliver says. But, she adds, such transparencies are hard to achieve.
Google, for example, recently updated its privacy policy to say that anything on the public internet will be used as training data. “Obviously, technology companies have to respond to their economic interests, so their decisions are not necessarily going to be the best for society and for the environment,” Oliver says. “And that’s why we need strong research institutions and civil society institutions to push for actions.” ELLIS also advocates for data centers to be built in locations where the energy can be produced sustainably.
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement. “The only way to make sense of this data is using machine learning methods,” Oliver says.
Milner believes that the best way to expose AI-caused systemic inequalities is through people's stories. “In these last five years, so much of our work [at D4BL] has been creating new datasets, new data tools, bringing the data to life. To show the harms but also to continue to reclaim it as a tool for social change and for political change.” This change, she adds, will depend on whose hands it is in.