<aside> ⚠️ Warning: Use as Directed Although some projects cited in this report are from outside the US, the paper is heavily US-biased since the goal is to create policy recommendations in the US context. Tools and recommendations that work in the US should not be applied uncritically to other contexts, particularly Global South contexts, where the same tools could lead to neocolonial coercion towards western-style farming practices and the devaluation of indigenous knowledge systems. In all contexts, governance and technological tools should be used only when needed and directed by the beneficiaries, and never assumed to have greater truth than other ways of knowing.
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<aside> 💡 About the Author My name is Maya Cohen. I am a farmer, researcher and food sovereignty advocate with a passion for studying the relationship between science/technology and society. I wrote this report during an internship at Friends of the Earth US, when I was inspired by my colleague’s work on agricultural data regulation to explore alternative uses of data for food sovereignty as a tool to fight back against corporate-led digitalization.
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<aside> 💡 Thank you to Robert Cazemier, Shefali Girish, Nathan Dorn, Greg Austic, Jamie Gaehring, Pamela Charlick, Natasha Nicholson, Julian Tait, Mike Parker, Laurie Wayne, and Elizabeth Vaughan who generously donated their time to research interviews.
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This report reviews the projects, governance frameworks, and technological tools that are facilitating the use of agricultural data for real food sovereignty solutions, while upholding the rights of data subjects. From this review and 10 interviews with leaders creating these solutions, I recommend a number of policies that would support the use of agricultural data for food sovereignty and agroecology. Data can refer to any type of codified observations, including non-digital forms of data collection that have long been involved in traditional agroecology systems, but this report focuses on digital data to understand if this new technology has a role in food sovereignty.
What’s the problem with the status quo?
US policy is currently supporting a trajectory for digital agriculture that will worsen consolidation throughout the food system and reduce farmers’ power into a situation similar to that of gig workers. Over the last ten years, Big Ag companies such as John Deere, Syngenta and Bayer have announced a shift in their strategy towards emulating Big Tech. This transformation is beginning with integrated Internet of Things (IoT) agricultural machinery such as autonomous tractors and drone sprayers, that collect mass amounts of farm data and are directed by AI recommendations. Types of data collected include soil metrics, planting time, seed density, seed type, agrochemical applications, irrigation, yields, labor, finances, profits and losses. This data is often sent to digital agriculture platforms, software where farmers’ data is collected and farmers are given personalized recommendations by the digital agriculture providers that will supposedly improve yields and promote sustainability. Many digital agriculture subscriptions are additionally paired with carbon or other ecosystems service credit programs, which give farmers some compensation for implementing practices that digital agriculture providers claim will increase carbon sequestration.
Digital agriculture is promoted and funded by the federal government, corporations and environmentalists alike who claim it brings climate solutions with minimal regulation. However, the most common data collection tools are owned by AgTech monopolies like John Deere, and the most common digital agriculture softwares are led by agrochemical giants such as Bayer, allowing these actors with major conflicts of interests and questionable environmental track records to define sustainable farming through their data-based recommendations. In the hands of these monopoly-like companies, recommendations mean pushing affiliated products (read: toxic pesticides and fossil-fueled machines), while any carbon sequestration achieved will be countered by the sales of offsets that excuse other polluters. With no regulations to prevent digital agriculture from abusing farmers' data for anticompetitive means, platforms disempower farmers by moving intelligence from the hands of the farmers into a corporate controlled algorithm, similar to the situation of gig workers.
Consolidation is already a worsening crisis in the food system, and the status quo of digital transformation is poised to worsen that consolidation. Digital agriculture has the potential to increase consolidation in land and farm ownership, seeds and inputs, ecosystem services markets, and digital agriculture itself.
What are the alternative solutions?
The potential harms of the status quo show the immense power of data, especially in an environment of climate volatility. Resisting an extractive data ecosystem means returning the power of data back to the people creating that data. This process will take more than regulation to decrease exploitation by data collectors. It will require an alternative system with alternative technology and governance that empowers data subjects — the people who’s information and labor are represented in data — to choose what data is collected and how it is used. Potential uses of data for food sovereignty include farmer-to-farmer knowledge exchange, sharing information on accessible and just climate adaptation strategies and resilient seed varieties, civil society monitoring of corporate and government actions, and increasing small farmers’ viability via equitable access to markets and credit.
In order for data to be used for food sovereignty, it must be justly and democratically governed with the leadership of food systems workers, food consumers, and food producing communities whose knowledge, labor, and land is represented in data. The Open Data Institute suggests three types of bottom-up data governance: individual, delegated and collective. These types of governance are not mutually exclusive, and all have their place depending on context. Individual data governance solutions focus on the rights, ownership and privacy of data subjects, often through policies implementing statutory data rights. These policies create the legal infrastructure for data subjects to take control over their data. Delegated data governance solutions, such as data trusts, hand over the responsibility of data stewardship from data subjects to an expert or trustee with a mandate to act in the data subjects’ best interest. These solutions work best as an intermediary between data subjects and potential extractivist data collectors, by bringing in technical expertise to enforce data rights. Collective governance projects, such as data cooperatives, bring together data subjects to aggregate and manage their data. This model works best when data subjects have chosen to collect the data, and have time to invest in managing their data. All these solutions must address the balance between the need to respect data privacy, while working to create data commons for the public good.
An ecosystem of data collection and analysis that serves food sovereignty and upholds data rights requires technology that is specifically designed for this system, just as the status quo of extractive data governance is paired with data collection hardware and data management software that is built to serve data extraction. In addition to bottom-up data governance, a just data ecosystem requires equitable and relevant data; decentralized, adaptable, and accessible data collection tools; and flexible data storage.
Effective governance and technological solutions must be community-created, so the solutions themselves cannot be created through policy. However, the policies suggested at the end of this report can help community-created solutions to overcome obstacles that have led to low adoption, including a lack of funding and a need for technical literacy in communities. Given an utter lack of digital rights legislation at the federal level, the first step is to legally define data subjects and their rights to choose what data is collected and who has access to it. Further steps include requiring public access to data in certain situations, whether that is public access to data created through USDA funding, public access to corporate metadata so the public can monitor what data is being collected, or public access to data that is necessary for public safety. Policy must begin to recognize data as the influential and valuable asset that it is, which includes taxing data and using that money to fund community-based data solutions. These suggestions are a first step to modernize federal policy to empower farmers, food systems workers, and consumers through increasing digitalization of the food system.