Concurrent Session 3: Cooperative Infrastructure

First round of concurrent sessions

Format: Case in Progress (15 min each: ~7 min present + ~7 min audience)

Speakers: Keno Jüchems, Naveen Singh, Mansur Iumagulov, Kanikka Sersia, My-Phuong Nguyen-Hoang

AI changes more than who does the work. It changes how an organization plans, shares what it knows, and decides what to do next. Keno Jüchems argues that cooperatives are well placed to lead this shift. Members could use AI to coordinate across a large organization, to put information in everyone’s hands, and to spread decisions out instead of sending them up a chain of managers. A cooperative can try out new AI workflows without using them to replace workers, so jobs change and the people stay. If cooperatives build these tools and sell them, other organizations will adopt AI on cooperative terms. Venture capital is already designing the companies of the AI era. Jüchems asks how cooperatives can get there first.

Mansur Iumagulov’s cooperative uses AI to help members collaborate and to distribute credit fairly for what they create together. When a small group meets, the AI records who originated each idea. It identifies points where the group’s positions conflict. It gives every participant a fair summary of their contribution, calculated from five criteria. The AI then helps the group draft explicit mutual commitments. A nine-point checklist allows members to assess how effectively they are cooperating. A fair-share mechanism determines how the group owns and rewards shared concepts, designs, and other creative output. The AI is accountable to the members, not to an employer or external platform, and the credit allocation process remains transparent to all. This is solidarity AI in action: technology that enables people to retain ownership of what they build collectively, rather than surrendering it to companies that extract value.

Kanikka Sersia examines Namma Yatri, the zero-commission ride-hailing app built for Bengaluru’s auto-rickshaw drivers, as a test case for Solidarity AI. Drawing on her doctoral research on how the platform economy is regulated, she asks which cooperative principles the platform puts into practice, where code and law pull in different directions, and what its model means for drivers who want a real say over the systems that dispatch and price their work.

My-Phuong Nguyen-Hoang asks how agricultural cooperatives in Vietnam’s Mekong Delta could become community data commons for climate risk governance. Farm data is now collected for traceability, insurance, emissions monitoring, and credit, but it sits scattered across state agencies, technology providers, insurers, and short-term projects, while farmers have little say in how it is used. Drawing on commons theory and cooperative principles, she proposes cooperatives as democratic intermediaries that gather, govern, and negotiate data on behalf of their members. She sets out what this would take: meaningful consent, clear data rights, shared standards, fair benefit-sharing, and the collective power to refuse extractive data deals.

Community notes

Reporter 1: Keno Jüchems
Reporter 2:

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