This chapter redefines data sovereignty as a foundational issue for democratic renewal in the GenAI era, critically engaging with the monopolistic power of Big Tech platforms—or “data-opolies”—that dominate political discourse, elections, and civic life. It argues that such corporate power erodes democratic accountability and reshapes political agency through opaque algorithmic systems, predictive analytics, and infrastructural asymmetries. Drawing on insights from innovation systems and institutional theories, particularly the work of Karl Polanyi and Richard R. Nelson, the chapter reframes data sovereignty as a multilevel, polycentric, and dynamic construct—civic, communal, institutional, and transnational in scope. Rather than accepting market-led, extractive models as inevitable, the chapter foregrounds emancipatory alternatives: data cooperatives, public-interest digital commons, and AI accountability mechanisms embedded in civic deliberation. These models seek to reclaim data as a democratic and collective resource, challenging the logic of commodification that drives current AI economic systems. Empirical evidence from urban data infrastructures and electoral practices underscores the urgency of establishing sovereign, participatory digital ecosystems—especially for smaller cities and vulnerable polities. Ultimately, the chapter offers a roadmap for policymakers and civil society to rearticulate data governance, recoding digital power toward equity, transparency, and democratic agency in datafied democracies.

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What Do We Mean by Data Sovereignties?

  • Igor Calzada

摘要

This chapter redefines data sovereignty as a foundational issue for democratic renewal in the GenAI era, critically engaging with the monopolistic power of Big Tech platforms—or “data-opolies”—that dominate political discourse, elections, and civic life. It argues that such corporate power erodes democratic accountability and reshapes political agency through opaque algorithmic systems, predictive analytics, and infrastructural asymmetries. Drawing on insights from innovation systems and institutional theories, particularly the work of Karl Polanyi and Richard R. Nelson, the chapter reframes data sovereignty as a multilevel, polycentric, and dynamic construct—civic, communal, institutional, and transnational in scope. Rather than accepting market-led, extractive models as inevitable, the chapter foregrounds emancipatory alternatives: data cooperatives, public-interest digital commons, and AI accountability mechanisms embedded in civic deliberation. These models seek to reclaim data as a democratic and collective resource, challenging the logic of commodification that drives current AI economic systems. Empirical evidence from urban data infrastructures and electoral practices underscores the urgency of establishing sovereign, participatory digital ecosystems—especially for smaller cities and vulnerable polities. Ultimately, the chapter offers a roadmap for policymakers and civil society to rearticulate data governance, recoding digital power toward equity, transparency, and democratic agency in datafied democracies.