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Paper short abstract

The paper draws on “digital degrowth” ideas to conceptualise alternative infrastructure models of AI/digital economy and society that go beyond digital monopolies with profit-making orientation and are informed by different governance models and a strong role for the state.

Paper long abstract

The consolidation of “cannibal capitalism” (Fraser), “surveillance capitalism” (Zuboff), or “platform capitalism” (Srnicek), to mention a few of its nominations, creates the need for new understandings of the intricate relationship between digital technologies, data power and the economic models that underpin digital infrastructures.

To be sure, connections between profit-making technological developments, the monopoly character of the digital economy and environmental impacts have been challenged through alternative models around the commons, peer-production, convivial technological development, and bottom-up platform models informed by cooperative logic. However, these have not hitherto enjoyed generalised use.

Drawing on conceptualisations around the notions of “digital degrowth” (Saito, Kwet), the paper argues for the need of a redesign of digital, AI-based capitalist economy and the associated infrastructure. The paper calls for a renewal of thinking in technological/AI development that is less informed by big tech/AI infrastructures and monopolies and more based on community-based co-production and peer-based innovation and less on profit-making innovation.

Taken together, the above directions constitute a new roadmap for digital technology (including AI) development and governance, for controlled data accumulation and processing, in accordance with societal needs and respect for environmental implications. The implementation of this necessitates a strong role for the state to resist over-investment in concentrated data centres, notably in developing countries. The paper ends by arguing for the urgency to build advocacy and communicative strategies making the above connections clear and pointing to workable technological alternatives that are resilient from a social and data governance perspective, as well as environmentally sustainable.