Centering Equity and Justice in Global Data Governance is a collaborative research initiative led by IT for Change, with support from the Fair, Green and Global Alliance and the Centre for Global Digital Justice. The project brings together a dynamic group of scholar-practitioners who are critically engaging with pressing debates at the intersection of data justice and longstanding development challenges.
Our partners, ETC Group, FIAN International, Open Knowledge Foundation, People's Health Movement, and Third World Network, are developing case studies on digitization and datafication across critical sectors, including public health, biodiversity, food sovereignty, knowledge commons, and climate action.
Through these case studies, the project aims to bring out the economic, social, and cultural rights (ESCR) violations and socio-economic injustices stemming from corporate impunity, lack of respect for domestic law, and exploitation of loopholes in international and national regimes, including, but not limited to, trade, IP, and data governance. Based on these insights, the project aims to articulate justice-oriented approaches to data governance and advance sector-specific, contextually grounded data justice principles rooted in Global South perspectives.
Case Study Reports
ETC Group
1. Commons to Code: How Platforms Rewire Agriculture and Reshape Power
This case study examines the rise of digitalized, data-dependent agriculture and examines Bayer’s Climate FieldView platform as a paradigmatic example of how agribusiness and technology corporations are reshaping food systems. The study maps the agricultural data pipeline—from data generation on farms to its storage, processing, and monetization—showing how each stage is embedded in corporate-controlled infrastructures and contractual regimes. The study identifies risks to food sovereignty, cultural rights, labor, health, and the environment. It argues that prevailing models of “ownership” and voluntary governance are insufficient, as they obscure issues of control, accountability, and justice. Instead, it calls for structural data justice approaches, including collective data rights, public oversight of digital infrastructures, and community-centered governance frameworks to counter corporate capture.
2. AI’s Large Looting Models? The Emerging Generative Biology Stack as the Next Frontier of Biopiracy
This report sheds light on the emergent field of Generative Biology (GenBio), which is expanding at extraordinary speed, propelled by Big Tech and venture capital, with pharmaceuticals as its primary market and growing applications across agriculture, materials, and energy. Promoted as a transformative solution for health, food, and climate challenges, its greatest value may lie in serving the AI industry itself—generating data-heavy workloads and reputational benefits—while shifting social, ecological, and economic costs onto society. The study highlights urgent data justice concerns: renewed bioprospecting to feed AI models, the conversion of biodiversity into proprietary digital assets, erosion of consent and benefit-sharing, and the acceleration of digital biocolonialism, among many more. Against this backdrop, the report identifies key entry points for civil society engagement, including negotiations under the Convention on Biological Diversity, the FAO Seed Treaty, privacy and data protection enforcement, and national or regional policy on AI training data.
FIAN International
1. Seeing Everything from Nowhere: A Human Rights Assessment of the United Nations Food and Agriculture Organization’s Data Governance
This study critically examines the Food and Agriculture Organization’s (FAO) data governance framework, assessing its alignment with human rights principles and its implications for marginalized groups, including Indigenous Peoples, peasants, women, and workers. It evaluates whether FAO’s digital initiatives, particularly its digital public goods (DPGs) and digital public infrastructure (DPI), uphold equity, transparency, and participatory decision-making in agri-food systems. The analysis reveals significant gaps in FAO's current data governance model. A central concern is FAO's growing dependence on US-based technology corporations for cloud services and digital infrastructure. The research also highlights how FAO's DPGs and DPIs fail to meet key public interest criteria. The study concludes with concrete recommendations to align FAO's digital transformation with human rights and public interest principles and food sovereignty.