Data Co-ops: How Cooperative Structures Can Support Women’s Empowerment

Astha Kapoor November 03, 2022

(This blog post was cross-posted from the Future Development blog’s (The Brookings Institution) original post, which can be found here.)

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 decision-making 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 decision-making, 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.

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