







How do we share prosperity in society if work no longer sits at the center of people’s lives? In this essay, Anna Yelizarova explores one provocative possibility: a “global dividend.” If transformative AI shows little respect for national borders, with effects that spill across countries, then we ne
Built on Shared Knowledge: What the World Wants from AI Wealth
AI labs and policymakers are focusing on AI dividends to address economic insecurity. We asked 1,041 people across 64 countries what they actually want from AI wealth.

Strengthening AI Foundations: Emerging Opportunities for Developing Countries
The World Bank’s Digital Progress and Trends Report 2025 explores how AI is accelerating growth in developing countries, while highlighting persistent gaps in access, infrastructure, and skills. Discover key trends, challenges, and the ‘Four Cs’ needed to strengthen AI foundations globally.

March 2026 Global Dialogues Survey | Windfall Trust
Here’s what the world had to say about the AI economy

3: Consulting the Record: AI Consistently Fails the Public - AI Now Institute
Amid the excitement over AI’s (speculative, hypothetical) potential, we have lost sight of the sobering reality of its present and recent past. AI is already intermediating critical social infrastructures, materially reshaping our institutions in ways that ratchet up inequality and concentrate power in the hands of the already powerful. It is consistently deployed in ways […]

The Next Great Divergence: How AI could split the world again if we don’t intervene | Brookings
Michael Muthukrishna and Philip Schellekens argue that AI, like past general-purpose technologies, could drive a new global divergence unless deliberate action ensures its benefits are broadly shared rather than geographically concentrated.

From the Platform Society to the AI Society: Towards Critical Studies of Generative AI
The era of AI has begun. Generative AI is rapidly reshaping knowledge production, culture, and political authority, giving rise to an emerging AI society. Yet this transformation did not emerge ex nihilo. This paper argues that the AI society can only be understood in relation to the platform society from which it arises. Tracing the transition from platforms to AI, we identify interlinked economic, epistemic, and political shifts. Economically, AI emerges within platform-based rentier capitalism but reconfigures the monopoly mechanisms on which its accumulation depends. Epistemically, LLMs mark a shift from predictive to generative epistemics, entangling theory formation and knowledge production with private research-as-a-service infrastructures. Politically, governance shifts from data politics to alignment politics: from shaping visibility to shaping what can be said, thought, and imagined. Together, these transformations signal a qualitative shift in mediation—from governing interaction to governing cognition itself—and call for a Critical AI Studies.
AI Commons - One Project
What if we could redefine AI? What if we could shift its development from a capitalist model to a more disruptive, inclusive, and decentralized one?

New schemes teach the masses to build AI
Treating it like a craft is paying dividends

Digital Labor Platforms as Infrastructure of Extractivism
This chapter examines how digital platforms, as infrastructures of extractivism in contemporary artificial intelligence, enable corporations to appropriate data and labour while concentrating value in core regions such as Silicon Valley. It proposes platform extractivism as a framework linking commodification, epistemic dominance, and reproduction through territory. Drawing on digital labour studies, Latin American critical thought, and mixed-methods research with Venezuelan and Colombian data workers, the chapter discusses how AI depends on precarious platform labour to produce, clean, annotate, and maintain data. It further shows how annotation systems normalize culturally specific categories, especially US norms, as universal knowledge, reproducing colonial hierarchies. Finally, it highlights how data work is sustained by unpaid reproductive labour, community networks, and material conditions that make workers available for platform labour. Platform extractivism thus reveals AI as a labour-intensive and territorially embedded political-economic system under capitalism that perpetuates legacies of coloniality.

A Real Political Economy of Technology - The Ideas Letter
Two technological futures are competing for political and material priority: generative AI and the green transition. Benanav argues that while AI is marketed as a world-reordering breakthrough, its productivity gains…

AI, Decomputing and the Interregnum
This paper treats AI as diagnostic for the deeper changes taking place in the existing order of things. It uses AI's alignment with both the political economy and with the dualisms that underpin it, including race, gender and anthropocentrism, to highlight the nihilistic character of the current restructuring. AI's scaling and accelerationism are taken as examples of the wider tactics being invoked by hegemonic power to maintain control under changing conditions. From this perspective, the massive build-out of data centres isn't simply a seizure of energy resources but a manifestation of an aggressive and misogynist technopolitics. The paper argues that a liberal push for digital sovereignty doesn't interrupt these dynamics but plays into the hands of emerging technofascism. It proposes instead the prefigurative tactic of 'decomputing', which draws on degrowth, deautomatisation and a convivial approach to technology. It explores decomputing as a means to mitigate both material and relational harms and as a decisive turn towards infrastructuring the common good. The paper concludes that AI is the contradiction that reveals many others, not least the gap between claims to legitimacy and the actuality of destructive violence, and proposes an alternative technopolitics of reciprocity that prioritises care and sustainability.
AI, Decomputing and the Interregnum
This paper treats AI as diagnostic for the deeper changes taking place in the existing order of things. It uses AI's alignment with both the political economy and with the dualisms that underpin it, including race, gender and anthropocentrism, to highlight the nihilistic character of the current restructuring. AI's scaling and accelerationism are taken as examples of the wider tactics being invoked by hegemonic power to maintain control under changing conditions. From this perspective, the massive build-out of data centres isn't simply a seizure of energy resources but a manifestation of an aggressive and misogynist technopolitics. The paper argues that a liberal push for digital sovereignty doesn't interrupt these dynamics but plays into the hands of emerging technofascism. It proposes instead the prefigurative tactic of 'decomputing', which draws on degrowth, deautomatisation and a convivial approach to technology. It explores decomputing as a means to mitigate both material and relational harms and as a decisive turn towards infrastructuring the common good. The paper concludes that AI is the contradiction that reveals many others, not least the gap between claims to legitimacy and the actuality of destructive violence, and proposes an alternative technopolitics of reciprocity that prioritises care and sustainability.
Apocalypse Now and Then • EQUATOR
Artificial intelligence is capitalism’s final destination

Automate the C-Suite - The Ideas Letter
Weatherby argues that Benanav’s and Morozov’s essays on AI and the left miss a deeper reality: Today’s AI is not a neutral tool operating within capitalism but the materialization of…

The Scaling Era: An Oral History of AI, 2019–2025
An inside view of the AI revolution, from the people an…

"The forces that are now shaping AI are the same forces that turned the open internet into monopolistic platforms, converted peer-to-peer participation into precarious labor, and enclosed the digital commons. They are now threatening to capture and enclose thought itself." osf.io/preprints/socarxiv/qahd3_v1/