Unlocking the power of feminist data cooperatives

Digest #46

Members of the Megha Mandi cooperative farming rice. Credit: Megha Mandli via Bapu Vaitla.

A powerful movement is sweeping through the world of development cooperation, as experts and practitioners embrace a feminist approach to data. Development through a feminist lens demands a close examination of power structures and a commitment to tackling structural inequalities, discrimination, and unequal treatment head on.

As we strive to make this vision a reality, it’s clear that data plays a crucial role. But how can we ensure that data works for everyone, especially those from marginalized groups? What exactly is gender data, and how can it empower those who need it most? 

These are the questions that the GIZ Data Lab along with the Data Pop Alliance are seeking to address through a series of knowledge-sharing sessions to inspire and share applicable insights on Data Feminism by featuring experts from various sectors and working at multiple levels. 

In the spirit of International Women’s Day last week, we’re sharing insights from a recent workshop in the Data Feminism Series for anyone who’s looking to incorporate a feminist approach to data collection, production, and use. In this post, we seek to illuminate the potential of data cooperatives as a means of redistributing power. (For more on Data Feminism, see this description of the first workshop in the series.) 

Manifesting data feminism through data cooperatives

Data cooperatives allow groups of individuals to voluntarily pool their data. The members of the cooperative retain full control over their data and which insights are gathered from it. As such, data cooperatives are a potential solution to fill gender data gaps for policymakers while protecting privacy and redistributing power to individuals. This means that individuals have a greater say about privacy and can channel more detailed data to policymakers to address concerns in their own communities.  

Research by the Ada Lovelace Institute suggests that “data cooperatives could be the go-to governance mechanism when relationships are formed between peers or like-minded people who join forces to collectively steward their data and create one voice in relation to a company or institution.”

Even though there are few real-world examples of data cooperatives, the concept of a cooperative dates back to workers organizing during the Industrial Revolution. The structure of “one member, one vote” ensured that members had equal say in decision making and that benefits were distributed equitably. Cooperatives nowadays in sectors such as agriculture and housing have been shown to contribute to women’s empowerment, especially in the Global South where women’s cooperatives have catalyzed income growth among the poor.

For example, Megha Mandli is a women farmer’s cooperative in India with more than a thousand members who benefit from support for business-related planning and acquiring supplies like seeds or poultry feed. The Aapti Institute has developed a use case to show that pooling data from individual women farmers and their activities would allow women in Megha Mandli to benefit from the social and economic value of data while maintaining control over their own data.  

Adding a “data layer” to this cooperative’s existing structure would redistribute the economic benefits of data and add value through several channels. First, it would help pool data and demonstrate credit worthiness to digital financial service providers, allowing women to access credit. It could also give women farmers increased agency over their data. Members who control their data could use it to increase the value to their outputs (e.g., use irrigation or fertilization data to improve agricultural yields). Such a data cooperative would reduce the potential for AI-driven bias by allowing members to confirm the representativeness of underlying datasets. Finally, data could be pooled for farmers to share knowledge, learn about climate resilient practices, and obtain data-driven advice to increase agricultural output.  

A roadmap to support feminist data cooperatives

Data cooperatives offer potential benefits, but they also come with some risk (see examples in the chart below). Data2X, Aapti, and other partners are working to balance these risks and address existing structural and social barriers to establishing data cooperatives. 

Data2X, the Aapti Institute, and partners are working on a roadmap to manage these risks and scale up gender data cooperatives around the world. The roadmap has three main steps: creating educational resources, building a gender data cooperative incubator, and launching a Global Gender Data Cooperative to pool data on key transnational issues like migration, climate change, and human rights while building a network of solidarity and mutual support. 

To follow this work and learn how you can get involved, please email Bapu and Astha at BVaitla@data2x.org and astha@aapti.in!