It started with a simple but urgent question from farmers:
“Why do they want my data?”
That question stayed with IRES alumna Sarah-Louise Ruder, now a post-doctoral fellow at the University of Ottawa, as she conducted her Master’s research and became a catalyst for her broader exploration of data governance through the lens of agri-food movements. Around the same time, public debate on data governance was growing, particularly after the publication of Shoshana Zuboff’s The Age of Surveillance Capitalism in 2019.
The fields of data studies and data justice were taking off, drawing focus to social media platforms and governmental surveillance. Yet, as Ruder observed, there was little discussion about how agricultural data—which she was knew was being collected in vast quantities through tractors, field sensors, and farm management software—was being accessed, analyzed, and monetized by large firms.
Indeed, governments are increasingly asking farmers to share more data, especially around environmental concerns like nutrient management. And the private sector is racing ahead with new digital tools. But the question remains: who benefits?
As Ruder puts it:
“We are at a critical moment. Generative AI is being heralded as a transformative tool for solving complex challenges across sectors, including agriculture. In January, more than 150 Nobel and World Food Prize Laureates named AI among the ‘moonshot’ technologies necessary to feed the world by 2050. AI depends on data. So, decisions about how that data is collected, used, and governed will have profound effects on farmers, food systems, and the environment.”
Data, AI, and the agri-tech ecosystem
AI is not entirely new to agriculture. Its foundations were laid decades ago, with technologies such as satellite-steered tractors and yield monitors. Today’s farm machinery can use GPS to steer with precision, reducing inefficiencies. Early versions of yield-monitoring systems could tell farmers which parts of their field produced the most bushels per acre.
Now, platforms like Climate FieldView—owned by Bayer—go a step further. They offer predictive models that estimate potential yield and suggest products, often fertilizers or chemicals, that promise to improve output. “Unsurprisingly, the recommended products are typically owned by the same company that developed the software,” says Ruder.
This convergence of data collection, analytics, and product sales raises concerns about corporate control, transparency, and accountability. As innovation increases, so does the tension between technological progress and justice.
Confronting tensions through conversation
Through an analysis of 40 workshops, conferences, and community dialogues on agricultural technology and data governance, Ruder noticed that stakeholders often agree on the importance of innovation—but on how and by whom decisions were being made.
At AgSmart, an annual Alberta-based ag-tech conference, Ruder shared findings showing that farmers feel uneasy about how their data is being collected and used, especially by companies and governments. Industry representatives, many of whom were presenting their own technological solutions, expressed discomfort at being cast as untrustworthy.
Ruder sees this discomfort a starting point rather than as a dead-end. “People were responding not so much to each other, but to the systems of power I was highlighting,” she says.
Miscommunication is common. For instance, when the term “corporate power” is used in critical social sciences or justice movements, family farmers who run incorporated farms sometimes feel targeted, even though the critique is aimed at large multinational agribusinesses. These moments reveal a broader problem: agricultural data governance conversations are happening in silos between government, industry, and farmers without a shared language or space for mutual understanding.
“It’s not about accusing anyone of doing a bad job,” Ruder explains. “This is about emphasizing how many people across the food system don’t feel represented in these decisions, and how that feeds into a deeper lack of trust.”
The promise and limits of data governance “best practices”
To address concerns, the agricultural sector is borrowing data governance practices from other domains—like consent forms, data principles like “FAIR”, and regulatory compliance frameworks such as Europe’s General Data Protection Regulation (GDPR). But Ruder found that these tools often fall short for addressing agriculture’s unique power dynamics.
“More detailed consent forms won’t help if farmers can’t negotiate the terms, or if the language isn’t accessible,” she says. Even rights like data portability or the right to be forgotten have little impact without strong enforcement, capacity building, and meaningful mechanisms for recourse.
Representation is another critical issue. Predictive models trained on data from one region may produce misleading results when applied to another. For agricultural technology to be truly useful and fair, it must reflect the diversity of environments, practices, and experiences in the sector.
From principles to practice: what data justice looks like
So, what might data justice in agriculture look like? Ruder offers four interconnected strategies informed by her community-engaged research:
- Policy and legal reform,
- New data governance structures,
- Capacity building, and
- Solidarity across communities.
These are not quick fixes. Instead, they are building blocks for a more just digital future. “Having principles is one thing,” Ruder says. “Turning them into action is another.” That is why she highlights the role of grassroots organizations in grounding abstract principles in real-world practice.
Working with IRES’ Dr. Hannah Wittman and Shauna MacKinnon from the BC Agricultural Climate Action Research Network, Ruder led the development of an open access “toolkit” of practical resources about data governance in agriculture with this in mind.
Her publication with Wittman, Agricultural data governance from the ground up, is both a call to action and a metaphor for policies rooted in lived experience, close to the land, and accountable to the people who work it.
Data justice also means looking beyond the digital. Indigenous data sovereignty, labor justice for migrant farm workers, and ecological sustainability must all be part of the conversation. One group leading by example is OpenTEAM, an open-source collective working on a “data wallet” that gives farmers more control over their information. Another, Semillero de Ideas (Nursery of Ideas), collaborates with migrant workers across the Western U.S., centering their voices and expertise.
“Part of data justice is recognizing that people on the ground—the farmers, the workers—often understand the issues better than anyone,” Ruder explains. “It’s not just about who builds the algorithm. It’s about who gets to ask the questions in the first place.”
Rethinking the pace of innovation
But can slow, community-centered processes keep up with the fast-paced world of tech innovation?
Ruder challenges the assumption that innovation must be fast to be effective. She draws attention to evidence from history, which teaches us that rushed innovation often harms the most vulnerable. In the early 20th century, mechanized agriculture displaced thousands, contributing to ecological disasters like the Dust Bowl. Many farmers, particularly Black and Indigenous ones, were pushed out of markets they could no longer afford to keep up with.
“History shows us that when we move fast, bad things often happen. Still, innovation and change do not necessarily need to be slow,” says Ruder.
“They just have to be intentional.”
This means building relationships, honoring local knowledge, and moving at what community organizers call the pace of trust. When trust is present, things often move faster than expected.
Questions worth asking
As AI and big data continue to shape agriculture, perhaps the question is not what technology can do, but who it serves, who it excludes, and who gets to decide.
Will the next generation of agri-tech deepen existing inequities, or will it be guided by justice, collaboration, and care? Can we imagine innovation that uplifts rather than displaces?
And more provocatively: what would it look like if the future of food was not built by the fastest innovators, but by the most conscientious ones?
Text and image compiled by Nivretta Thatra, May 2025.