This presentation explores how artificial intelligence can be reoriented from an engine of extractive growth to a catalyst for post-growth, democratic, and relational futures. Drawing on degrowth theory, commons-based governance, and intersectional justice, it argues for a rupture with technocratic and capitalist logics embedded in prevailing AI infrastructures. It introduces the concept of Cooperative AI as both a political project and a design paradigm—one that fosters deliberation, care, and solidarity over efficiency and control. The keynote critically engages recent theoretical contributions (Staab and Sorg 2025) that diagnose the rise of “adaptive societies,” where digital innovation legitimizes expert-driven, depoliticized governance. Against this backdrop, it calls for a critical inquiry into the metaphysical assumptions driving the development of Artificial Intelligence, as well as derived technological, organizational and social innovations. The talk outlines key conditions for Cooperative AI, including degrowth-aligned functionality, commons stewardship, epistemic justice, and federated governance. It also foregrounds tensions—such as co-optation risks, symbolic inclusion, and infrastructural inequality—while identifying pathways for transformation through cross-sectoral alliances and participatory design. Ultimately, the address positions Cooperative AI as a site of ontological and political experimentation. Rather than scaling automation or productivity, it proposes AI as a medium for collective worldmaking—where technology becomes accountable to communities, aligned with planetary limits, and shaped by the ethical imperative to “stay with the trouble.”

--

Artificial Intelligence,Cooperativism,Post-growth,Relational Ontologies,Cybernetics,Innovation Ecosystems