By John Bliss
Imagine you are walking into your apple orchard on a beautiful June morning. The trees look good, but just to confirm your assessment, you glance down at a ring on your finger. The ring has a softly glowing orb of shifting colors, and you notice the colors blush from blue to a greenish yellow. It’s a subtle shift, but the color indicates the overall health of the field and it is significant enough to warrant a closer look. You engage a second wearable device strapped onto your forearm. These two devices are connected wirelessly to a dozen sensors throughout the orchard that are processing data: soil moisture levels, insect activity, and photosynthetic activity in the uppermost canopy, among other parameters. You are also looking carefully and smelling and listening, as farmers have done for centuries before you, but the wearable device allows you to ascertain the health status of all the different areas of the orchard. By simply gesturing your arm in the direction of the row of Liberty apples or the Northern Spy you can receive different data that helps you understand the cultivars’ relative well-being. The device gently delivers subtle vibration to the underside of your arm, allowing you to “feel” the data of the different sensors. Over the last few seasons you have learned to interpret the vibrations. With practice, interpretation has merged into a more intuitive understanding. After a few minutes, you have identified that, among several other stresses, the orchard is responding to a nutrient load. The rain from the night before must be flushing nitrogen from the fresh compost you spread the previous week.
This is one of the science fiction futures conjured up at a conference recently held in New York called Gathering for Open Agricultural Technology or GOAT. About 60 participants from many backgrounds came together to demonstrate projects, discuss the challenges of agricultural technology and, most of all, imagine what the future holds for agriculture. What technologies could farmers use to limit the use of inputs like fertilizer? What decision-making tools could facilitate sustainable practices? But also, who is technology ultimately for? How are democratic principles or social equity hindered or encouraged by algorithmic systems?
GOAT 2022 was only the second such in-person meeting since the group’s inception in 2018 and, as is often the case with nascent organizations, the creative energy was effervescent and palpable. Many people were meeting face to face for the first time, having contributed over virtual sessions to the same project or shared ideas through an online forum over the last several years of COVID-19. Some of the first conference topics were basically attempts at understanding the existing networks and “landscapes”: who was working on what; and what values might bind the community together under a shared vision or at least a common narrative.
The “O” in GOAT stands for “Open,” which means “open source.” In the software sense, open source implies that users have the right to inspect, share and modify the software for their purposes. There are deep parallels between the organic agriculture movement and the open source movement in the United States. They both date their conceptual birth to the 1960s where networks of like-minded individuals were forming. A maturity of sorts came in the 1990s as the National Organic Program (NOP) standardized rules and the Open Source Initiative formalized licensing. Both movements featured difficult debates over the values of the organizations’ coalescing around their principles, especially in relation to capitalism. In the past 30 years, the pace of change and growth within each community has obscured the common threads, and overlap between the two remains scarce. GOAT, being focused on agricultural technology, is positioned to be a bridge between open source technology and sustainable agriculture. This is what made this conference so unique.
The Roots of GOAT
GOAT became an established community six years ago, building on the previous work of agricultural tool projects like Farm Hack and events like Stone Barn’s Slow Tools conference. Many farmer-led innovation groups have focused on hardware tools like small-scale cultivators or home-made versions of expensive tools like chicken pluckers. Any tool that engages with automation (e.g., thermostats or motor controllers) involves electrical engineering, and in 2012 Farm Hack featured “Fido,” a greenhouse monitoring system using an Arduino microcontroller. Other small-scale open technology emerged at the same time: hand-held nutrient refractometers, data-loggers and aerial photo analysis tools.
Some early collaborators included Our Sci (analytic tools) and farmOS (farm management software), as well as various academic and farmer researchers. High-tech innovation is hard to track historically because it is too close to the present moment. We lack the perspective of decades to help us recognize the important moments. Progress is also intensely networked. Cross-pollinated and convergent projects paint a picture of an inspired collective, but as the community migrated towards software, GOAT emerged with fewer farmers and more developers and researchers. Thus, one of the topics at the conference was: How to involve more farmers in design?
From oral traditions to almanacs, from textbooks to online videos, farmers have always had plenty of sources from which to learn about agricultural practices. Learning about high technology on the other hand necessarily situates us in the contemporary moment. For those agrarians among us, this can be an uncomfortable space. Farmers are continually innovating (responding to the environment is a full-time job), but their risk-taking is tempered by an awareness that historically agricultural development is a top-down, often exclusive, state of affairs. Exclusion generally has pointed to technology being complicit in agricultural consolidation.
The open source movement, as expressed at the GOAT conference, makes an explicit attempt in engaging and collaborating with small-scale, under-resourced farmers in an effort to decentralize and democratize technology. GOAT is gaining strength by networking among international development nongovernmental organizations working to raise the livelihoods of small-scale farmers. One such organization, Digital Green, started out using video to boost farmer education in rural India. It is now engaged more deeply in market data-sharing tools, which aim to empower farmers who otherwise have very little access to knowledge of regional markets. Even many subsistence farmers are likely to have access to smartphones and already use generalized programs like WhatsApp to market products. NGOs working with open source software are trying to bring efficiencies to complex informal markets, thereby reducing food waste (currently estimated at one-third of all food production according to the World Food Programme) and elevating livelihoods. How exactly this will happen is still not clear.
Predictably, agribusiness has fully penetrated larger-scale farms with proprietary management software using sensor and hardware integrations. These technologies have resulted in precision agriculture, with the promise of decreasing waste and maximizing production, if not actual profits. It has become clear that the harvesting and privatization of data is more lucrative for the John Deeres of the world, rather than allowing for a more democratic approach. In this way the digital revolution does not look at all different from the Green Revolution. Whether or not open source represents a truly new direction in agricultural technology remains to be seen.
Who Benefits from Data
Technological openness is irrelevant to a farmer who has not achieved technological literacy first. Literacy is a word that does not fully describe the challenge of understanding technology: the pace of change requires continual engagement. Are farmers able to dedicate time to “keep up” with the technology? A farm “hardware” tool such as a cultivator will remain relevant and dependable for decades, but software is constantly updated and subject to sweeping changes with consequences for the user. As software is gradually integrated with tractors, precision planters or sprayers, the farmer is unexpectedly confronted with software literacy. These power imbalances are further enforced through licensing and warranty agreements that prevent a farmer from modifying or fixing a machine. A “Right to Repair” movement has thus emerged, which is in alignment with the open source ethic.
But even more consequential issues become apparent as technology companies handle troves of our information — from the details we provide them, to the data gathered through tracking and sensory capabilities. One farm management program, LiteFarm, gathers hundreds of data points: field locations, types of geography, soil qualities, cultivation practices, planting methods, seed sources, varieties planted, harvest yields, prices, revenues … Any and all information that is freely provided to the program is shared with and used by researchers ranging from university students to policy makers. This example is among the most benign given that the data is anonymized and openly provided as opposed to being identifiable and gathered through less transparent means. This data in the hands of profiteers higher up in the value chain, however, leaves farmers at risk of exploitation or worse.
Since software can, like a virus, be rapidly reproduced and then overlaid on anything connected to our global economy, the threats to environmental sustainability are profound. Expropriating data takes mere seconds with a few lines of code. Data extracted from farm laborers and land management in its raw form is a kind of colonialism. Who benefits from these data riches? What policy changes will be justified? What and who become expendable in the new rationalism of data analysis? These questions of data sovereignty are closely aligned with movements against corporate ownership of crop genetics and the appropriation of Indigenous cultural heritage.
Tagging my movements around the farm with geolocation will certainly reveal inefficiencies in the layout of my working landscape. Farmworkers can welcome such insight, leading to easier work and higher income. But when this data is aggregated and rationalized at a global corporate scale, decisions may be made that can profoundly impact the farmworkers who provided that data, such as restructuring of product lines or limitation of service regions. Rather than seeing workers’ inherent value in a process that could be more efficient, the capitalist vision may work towards the elimination of said process altogether. Of course, this is nothing new but data allows for an intensification of this scientific management. At the outset of the wide implementation of farm data collection, we should take a stand for the human-scale: the intrinsic potential of farmworkers rather than their elimination.
The Farmer and the Developer
Those of us in the world of sustainable agriculture might not see a reliable partner in software developers, open source or otherwise. True, many farmers take full advantage of spreadsheets to plan our season. Software for accounting (QuickBooks), commerce (Shopify) and marketing (Instagram) are nearly as ubiquitous in our small businesses as they are throughout our economy. But “solidarity” is hardly a term that characterizes these relationships. The culture of software development, especially of Silicon Valley, is often antithetical to that of sustainable farming. The “move fast and break things” motto of Facebook founder Mark Zuckerberg puts real people at risk for the sake of profit.
GOAT faces an uphill battle in bridging the divide between the farmer and the developer. Trust, the baseline for all relationships, will have to be a primary focus if the open technology community and that of sustainable agriculture are to find solidarity into the future. Some impetus may emerge from a third party — that elephant in the room — the consumers. Just as the organic farming movement grew out of consumer-producer conversation, the people who buy and eat our food will also require a seat at this table.
The agronomic mood ring may be just as functionally realistic as a carnival prize toy. But science fiction has long served as a forum for the dialectical imagination. Certainly, the case must be made for any kind of tech in any kind of agriculture. The optimism of flying cars and the end of disease must be proposed if we are to conjure also the dystopian consequences of positivist hubris. This conversational engagement is important for as wide a diversity of stakeholders as possible.
Contrary to stereotype, the back-to-the-land movement, which is often credited as the root of the organic agriculture movement, is a central example of this engagement. A clear and organized resistance to genetic engineering and chemical farming practices was (and is) bolstered by the human-scaled ecological example of those of us farming small plots and selling at local markets. The movement continues with innovation in no-till production, biodiverse cropping and scale-appropriate tools. In this sense, back-to-the-land and organic farming movements have never been a retreat from the challenging issues of the day. As digital innovation and disruptive technology flood our everyday lives, our local food and farming businesses can look towards networks like GOAT to be collaborators in achieving equitable outcomes. Afterall, sustainable farming moves slower and breaks fewer things. Thus, it is important for software engineers and designers to be reminded of our longstanding activism and willingness to propose — and debate — our agricultural vision.
John Bliss grows cut flowers and certified organic garlic in Scarborough, Maine, at Broadturn Farm. He can be reached at [email protected].
This article was published in the summer 2023 issue of The Maine Organic Farmer & Gardener, MOFGA’s quarterly publication.
