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“American farmers feed the world” is a phrase I have heard consistently since getting into agriculture, and despite the positive tone, it makes me feel uneasy.

One might think that the expression shows pride in what American farmers do, but that is not often the context in which it is used. American farmers certainly have a lot to take pride in, but there is more to this saying and others like it.

WASHINGTON – U.S. agribusiness spokesmen routinely defend practices that pollute air and water, and destroy soil by claiming that American farmers are doing what it takes to “feed the world.”

The facts tell a very different story. U.S. agriculture is not feeding the world’s impoverished and desperate people, according to a new EWG analysis of trade figures. Eighty-six percent of American agricultural exports in 2015 went to 20 of the world’s wealthiest and most developed export destinations, including Canada, China, Mexico and the European Union.

The AI Advantage: How Artificial Intelligence is Transforming Agriculture

Businesses are turning to artificial intelligence in the context of a rising global population and increasing pressure on international agricultural infrastructure.

Artificial intelligence in agriculture is not wholly new: nascent iterations have been in use for two decades, like auto-steering guidance systems to row crops such as corn. But AI take-up in the past few years has been swift; according to some estimates, 87% of businesses in the US agricultural industry were using AI in some shape or form as of late 2021. The federal government, too, is currently fast-tracking the agriculture industry towards the tech, providing financial incentives to speed up development and deployment of AI across the country.

If the push to adopt AI across the nearly two-million American farms succeeds, the implications for the rest of the world could be substantial. This is especially the case as the number of mouths to feed across the globe grows, and climate change threatens the agriculture ecosystems of some of the largest producers on Earth – including the US itself, which exported more than $100bn (£78.9b) of products to China, Mexico, Canada and Europe last year alone.

Agriculture is a cornerstone of human civilization, a testament to our ability to harness nature for sustenance. Yet, this age-old industry faces many challenges that hamper productivity, impact livelihoods, and threaten global food security.

By 2050, we must produce 60 percent more food to feed a world population of 9.3 billion, reports the Food and Agriculture Organization. Given the current industry challenges, doing that with a farming-as-usual approach could be tricky. Moreover, this would extend the heavy toll we already place on our natural resources.

American farmers are rapidly ploughing ahead with adopting artificial intelligence. The technology is as sophisticated as it is essential.

Standing in a lush green field in the American Midwest, a farmer points his smartphone at one of his soybean plants. He snaps a photo of a pest crawling a leaf, then lets an AI-driven programme name the species of the bug, and say whether it's a cause for concern. Technology like this might sound like a novelty – but it is vital.

Projections from the U.S. Department of Agriculture say net farm income is expected to decrease $43.1 billion in 2024 compared with 2023 – the largest year-to-year drop in history.

“It aligns with what we have been seeing because commodity prices have been dropping and expenses have been going up,” said Steve Ammerman, a spokesperson for the New York Farm Bureau.

But after four years of creative pivots to withstand unexpected hurdles that included financial stress, severe drought, and a global pandemic, Chang-Fleeman made a choice that many young farmers are considering: to leave farming behind. Why he left and what could have kept him on the land are critical questions we must address if we are to have a sustainable and food-secure future.

The USDA Census of Agriculture reported that in 2017, nearly 1 in 4 of the 3.4 million agricultural producers in the US were new and beginning farmers. Many of these new farmers are doing exactly what it seems American agriculture needs: starting small farms. According to the most recent data from the Agricultural Resource Management Survey (ARMS) in 2019, farms with annual sales of less than $100,000 accounted for about 85% of all U.S. farms. And though not all of these small-scale farms are necessarily organic, small farms are more likely to grow a diversity of crop types, use methods that reduce negative impacts on the climate, increase carbon sequestration, and tend to be more resilient in the face of climate change.

Between 2017 and 2022, the U.S. saw a reduction in farms by 141,733, a total decline of 7 percent. The trend, according to the USDA's 2022 Census of Agriculture, isn't isolated to specific states, with Texas, Oklahoma, and Missouri facing the most losses. American Farm Bureau Federation President Zippy Duvall issued a press release last Thursday addressing the challenges, attributing them partly to the flawed workforce system while advocating for the H-2A reforms to provide support to the agricultural sector.

"We are losing farms in America at a rapid pace and there is no question that our broken workforce system is partly to blame," Duvall said in the statement.

Gathering and examining huge data produced via IoT networks and wireless sensor networks, comprising digital images and more data from UAVs, satellites, and data fusion with existing data present difficulties to the effective execution of smart farming. Arising technologies about data mining techniques and artificial intelligence techniques are potential methods to achieve intuitions from said information [61], [63]–​[67]. These techniques can assist with dissecting greater and more unpredictable information, uncover covered-up models, and uncover trends quickly and precisely. The capability of these strategies in massive data investigation has not been sufficiently valued in farming for various reasons inspected underneath.

The greater part of the accessible open frameworks referenced already result from the latest projects, their issue is still extensively wide embraced, to conclude the final accomplishment. Large numbers of them may in any case be underdeveloped and have not attained their maximum capacity yet. Most of these applications of big data are suited for large industrial farms (such as Monsanto) that now employ big data in process of decision making and have the infrastructure to access data, resources, and most importantly access to finance [68]. There is very little work done on small farms around the developing world. Big data has the potential to support non-industrial farms, however moral and ethical queries regarding availability, cost, and funding need to be addressed to attain these advantages. If this trend continues, the benefits from data-driven precision agriculture will remain available to only big industrial farms.

The advent of precision agriculture has pushed the use of aerial systems in farming even further. Because precision ag focuses on spatial variability in crop production, getting accurate and timely measurements is crucial. Traditional aircraft has aided in these efforts, and modern drones have made this work faster, cheaper, and more accurate.

As a result, the market for agricultural drones is estimated to grow to more than $1 billion by 2024. Pushing this growth has been the increased use of drone technology to perform standard farming tasks, such as spraying crops with pesticides and fertilizer. Applications such as drone-based aerial mapping of growing areas are also pushing the technology forward in the farming world.

We conducted 3 types of analysis. First, for yields, biodiversity, resource-use efficiency and profitability, we examined “vote counts”, i.e., how many studies reported that smaller farms improved these outcomes versus not, and used hierarchical cumulative link models to synthesize these in probabilistic terms, i.e., what’s the probability that a study will find that farm size will have a particular outcome? Second, for a fewer set of studies for yields, resource-use efficiency, and profitability, where the studies reported regression coefficients for farm-size relationships, we conducted hierarchical meta-regressions to calculate pooled effect sizes summarizing the magnitude of change in outcome per 1 ha change in farm size. Pooled effects sizes were also calculated for GHG emissions using robust linear mixed-effects models.

So, what did we find? 79% of studies reviewed reported that smaller farms have higher yields, with yields increasing 5% per 1ha decrease in farm size. This is not an altogether surprising result – the inverse farm size-productivity relationship has fascinated agricultural economists for nearly a century, first reported by Chayanov in 1926. We also showed in a previous study that smaller farms have higher crop species richness; in that study we further found that smaller farms and larger farms grow a different portfolio of crops, and therefore, crop diversity at landscape scale may best benefit from having a mix of farm sizes. Our study also found that non-crop biodiversity increases with decreasing farm size, with 77% of studies finding that smaller farms have greater biodiversity at both farm and landscape scales. The primary studies we reviewed suggest that this is because of more ecological management practices on smaller farms (lower pesticide use, organic management, etc.), edge effects (smaller farms having larger margins that support biodiversity), or more diverse land cover in small-farming dominated landscapes. Our study found no statistical evidence for farm-size relationships with resource-use efficiency, greenhouse gas emissions, or profitability. We should note that we do not assess causality directly, i.e., that farm size is driving all the outcomes we reviewed (thanks to a reviewer for helping us clarify this in our paper). However, with both yields and biodiversity, we do believe there is strong theoretical support for a causal relationship as evidenced in the primary literature we reviewed.

We hear a lot about how we’re running out of antibiotics. But we are also doomed to run out of pesticides, because insects inevitably develop resistance, whether toxic chemicals are sprayed directly or genetically engineered into the plants.

Worse yet, weeds, insects, and fungus develop resistance in just 5 years on average, which has caused the chemicals to grow increasingly lethal over the past 60 years. And it takes on average eight to ten years to identify, test, and develop a new pesticide, though that isn’t long enough to discover the long-term toxicity to humans and other organisms.

The methods underpinning the state-of-the-art artificial intelligence systems are systematically vulnerable to a new type of cybersecurity attack called an “artificial intelligence attack.” Using this attack, adversaries can manipulate these systems in order to alter their behavior to serve a malicious end goal. As artificial intelligence systems are further integrated into critical components of society, these artificial intelligence attacks represent an emerging and systematic vulnerability with the potential to have significant effects on the security of the country.

These “AI attacks” are fundamentally different from traditional cyberattacks.

Researchers have puzzled over the slow adoption of precision agriculture by small-scale farmers. By recording the decision paths such farmers have to make along the implementation process of deploying for the first time site-specific fertilization, it was possible to show, using a prototypical small farm model, that farms with outdated, non-retrofittable technology are effectively excluded from digitization, as it will never be profitable over the lifetime of the precision technology. This results primarily from the high financial outlay for new equipment, and far less from the working time required for implementation.

Furthermore, it became evident that even when retrofittable mechanization is available, the investment is at the limit of a profitable use at the current costs and the model farm size. If a farm already uses digital technology that can be used for precision agricultural management at modest cost, or if a farm contracts out the site-specific fertilization program, then a positive linear effect in the operational result can be observed, delivering from 151.33 to 192.17 € ha−1 of accumulated added revenue at the end of useful technology life.

Mr. Negroponte noted the United States plays a critical role in global agriculture as the world’s largest producer of beef, soybeans, corn and poultry and a top exporter of a diverse group of foods such as almonds, apples, raisins, sorghum, pork and wheat. He also said the United States may need to be able to secure the safety and availability of food supplies of important allies such as Japan.

Mr. Negroponte said rising competition among countries and regions for finite resources such as water and arable land could hurt political stability and force U.S. military priorities to shift. He pointed to Syria and Iraq as currently being vulnerable to water scarcity because rivers, canals and dams are military targets.

Obviously, the rural healthcare situation matters in terms of food and energy security at home, but also in terms of economics—the United States is by far the largest global exporter of food, with roughly $40 billion separating America from number two, and is on the cusp of ending energy imports for the first time since 1950.

Des Moines, Iowa, October 24, 2023 – Agriculture Secretary Tom Vilsack announced today that the U.S. Department of Agriculture (USDA) is providing $2.3 billion to help American producers maintain and develop markets for their commodities and use U.S. commodities to bolster international food aid.

Consistent with a bipartisan request from the Senate Committee on Agriculture, Nutrition, and Forestry, USDA is utilizing funds from the  (CCC) to address challenges related to trade and food insecurity impacting U.S. farmers and the international community. USDA will use:

USAID is advancing global food security by helping families and individuals meet their need for a reliable source of quality food and sufficient resources to produce or purchase it. This, in turn, supports global stability and prosperity. By addressing the root causes of hunger, USAID is increasing economic opportunity and growth among vulnerable communities.

What is Food Security?

Although there may at first glance appear to be no close linkage between weapons of mass destruction and food, in the twenty-first century with world resources of food, land and water under growing stress, nothing can be ruled out. Indeed, chemical weapons have frequently been deployed in the Syrian civil war, which had drought, agricultural failure and hunger among its early drivers. And nuclear conflict remains a distinct possibility in South Asia and the Middle East, especially, as these regions are already stressed in terms of food, land and water, and their nuclear firepower or access to nuclear materials is multiplying.

It remains an open question whether panicking regimes in Russia, the USA or even France would be ruthless enough to deploy atomic weapons in an attempt to quell invasion by tens of millions of desperate refugees, fleeing famine and climate chaos in their own homelands – but the possibility ought not to be ignored.