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.
March 2026 Global Dialogues Survey | Windfall Trust
Here’s what the world had to say about the AI economy
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?
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.
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…
AI Economy Institute - Microsoft Research
The AI Economy Institute (AIEI) is Microsoft’s flagship think tank dedicated to shaping an inclusive, trustworthy AI economy. We building a network of scholars and convening that network with our subject matter experts to explore how artificial intelligence is transforming work, education, and productivity – and making this knowledge base available to policy-makers, educators, and […]
AI’s Imperial Agenda
“Empire of AI” author Karen Hao on how Silicon Valley’s young AI companies parallel colonial empires of old.
Erik Brynjolfsson on Twitter / X
The @nytimes piece today by @ByrneEdsal13590 highlights a concern I share: “If we stay on the current path, the risk of extreme concentration — both economic and political — is very real.”In work with @zhitzig, we ask why AI may shift the balance between dispersed knowledge… pic.twitter.com/10vOTRj4Dq— Erik Brynjolfsson (@erikbryn) March 17, 2026
The Scaling Era: An Oral History of AI, 2019–2025
An inside view of the AI revolution, from the people and companies making it happen.
What we can’t measure about AI – yet | Aeon Essays
The costs of transformative innovations are immediately clear: it’s the longterm gains that are hardest to understand
"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/
