Data co-ops: How cooperative structures can support women’s empowerment

women working
Editor's note:

In the 17 Rooms 2022 flagship process, Astha Kapoor and Bapu Vaitla co-led Room 9, a working group on Sustainable Development Goal 9 for industry, innovation, and infrastructure.

Rising inequality and persistent social problems are forcing societies around the world to rethink dominant forms of economic organization. The most promising solution may be a tried-and-true one: cooperatives. Cooperatives are anchored in a set of globally agreed principles—open and voluntary membership; democratic member control; members’ economic participation; autonomy and independence; education, training and information; cooperation among cooperatives; and, most critically, concern for community.

Cooperatives are not a new structure. Cooperative movements gained pace in response to the Industrial Revolution, offering workers a mechanism to organize economic activity and enhance collective resilience. The cooperative structure of “one member, one vote” ensured that all members had equal weight in decisionmaking and benefits were distributed equitably. Cooperatives now play important roles across the world in sectors such as agriculture, insurance, and housing. They’ve also played a significant role in women’s empowerment, especially in the Global South, where women’s cooperatives have been key catalysts of income growth among the poor.

As the world enters the “Fourth Industrial Revolution”—the integration of physical, biological, and digital systems—the role of cooperatives in helping communities organize data resources is becoming more apparent. The idea of the “data cooperative” is slowly taking shape globally as a mechanism to rebalance power in the data economy and (re)create collective mechanisms to negotiate with technology companies and navigate questions on data rights. It is clear that data is a relational good: while our digital experiences may be individualized, the value of data derives from aggregation and insights about the relationships between individuals—and the harms from data use also happen at a collective or group level. In this context, the cooperative model offers a powerful institutional structure to responsibly steward the data of its members, safeguarding their interests while generating collective value. The cooperative principles mentioned earlier highlight collective decisionmaking, redistributing value, digital literacy, and prioritizing community interests, which are all critical considerations in effective data governance.

Examples of successful data cooperatives already exist. MiData and Salus Coop enable their members to pool and share health data. Swash pools web surfing data from its members. Driver’s Seat is a driver-owned cooperative that aggregates work-related data from the smartphones of gig-economy workers. Resonate is a data cooperative collectively owned by musicians, labels, and fans. These co-ops also take on a fiduciary responsibility: a legal obligation to manage data, provide insights, and negotiate with service providers in the interest of members (which makes institutions with already existing fiduciary responsibilities—credit unions, for example—ideal starting points for scaling out data cooperatives).

Where does the data cooperative movement show the greatest potential for quickly scaling up? We mentioned earlier that women’s cooperatives—and other informally organized women’s collaboratives like self-help groups—play essential roles in promoting gender equality. These cooperatives typically pool labor (as in worker’s cooperatives), capital (as in micro-lending groups), or both. Data is another valuable asset that can be pooled for collective good. Individual members of co-ops are already passively or actively generating data, although in many cases the value of this data is captured solely by other entities—tech platforms, for example. Data cooperation would divert some of this value to individuals while proactively preventing harm.

Women’s cooperatives are a promising focus for the data cooperative movement for three major reasons. First, the “infrastructure of trust” is already built. Cooperatives can be complex to manage, not least because collective decisionmaking requires strong relationships. While women’s cooperatives vary in their quality of governance, the shared experience of building and sustaining a novel organization in the face of gender-inequitable social norms is an encouraging foundation for taking the innovative step of building a data cooperative. Platforms for governance, decisionmaking, and collective action are already established, and existing cooperatives can view data rights as a cross-cutting concern across different aspects of their ongoing work. Offline trust mechanisms can be brought online.

Second, pooling data can help overcome gendered socio-economic obstacles. For example, access to credit is particularly difficult for women farmers, in part because the lack of data on women small-holder operations complicates credit scoring by financial service providers (FSPs). One women’s farmer cooperative we work with in Gujarat, India, is pooling their income and credit history data in order to present a fuller picture of creditworthiness to FSPs. This more robust digital economic identity can also help with access to loans for non-agricultural expenses such as education. Women across the world are often invisible to both market and state actors in part because of the incompleteness of data systems. Data cooperatives can remedy this situation.

Third, pooling data puts women in a stronger position to negotiate for their interests. This facilitates, for example, privacy protection through data aggregation. More broadly, in offering a means to transfer power from data controllers and users to individual women and girls, the data cooperative model hews to the principles of data feminism. In addition, women can exercise greater control over the flow of data to the public sector, supporting policies aimed at enhancing gender equity.

The potential of data cooperatives is immense. They offer a data stewardship model that empowers the marginalized to protect themselves from harm while reclaiming value from their digital lives. However, building data cooperatives is complex and requires significant investment in increasing digital literacy, building the data architecture, and developing effective, flexible consent mechanisms. We believe that, instead of creating data cooperatives from scratch, it is more prudent to enable existing women’s cooperatives to add a data layer to their current functioning, such that cooperative members with shared lived experiences can pool their data assets to derive more value and prevent harm. Such a strategy would bootstrap existing vehicles of empowerment. The data revolution is here. The challenge for the global community is to deploy the tools of this revolution within vehicles already known to be powerful instruments of change.