Abstract Beginning with the United States in 2016, more than 70 countries and international organizations have published strategies and policy recommendations for artificial intelligence (AI) infrastructures. This article locates these policies in the shift from a hierarchical distribution of power to a flatter diffusion of power in which systemic interactions can be top-down, bottom-up or horizontal. A diffusion of power across multiple actors and regions weakens the material and socialization capabilities of hegemonic actors, resulting in global governance outcomes that are described here as ‘multiplexity’. Multiplexity offers a complex and pluralist menu of choices to actors. The computational models employed in this article show complex networks and clusters around multiplex choices that outline patterns of global governance for the evolving AI infrastructures. These networks and clusters cast doubt on many of the extant theories of global governance: those rooted in material power, wherein hegemonic states shape global governance; those where normatively motivated actors shape governance in national contexts; or those where regional patterns (North–South, East–West) are easily discernible. The article locates the origins of multiplexity in a diffusion of power entailing intersecting networks, regions, actors and world-views. There are leaders and great powers in AI, but the rest are not merely followers. In a diffused power scenario, multiple ontologies about the world coexist. The article employs big data mining, specifically latent Dirichlet allocation models from computer science, and process tracing to provide evidence of governance mechanisms for AI.

Abstract This article analyses the role of online organic intellectuals in the consolidation of Bolsonarism within Brazil's ongoing neo-liberal order. Drawing on the Gramscian concept of passive revolution, it argues that far-right digital influencers act as key ideological mediators, channelling popular discontent, resentment and anti-systemic affect into cultural and moral narratives that ultimately stabilize the existing political economy. Rather than disrupting neo-liberalism, these figures repackage its legitimacy crisis through nationalist, anti-globalist and culturally conservative frames. The analysis traces this process in Brazil's recent political trajectory, from the gradual exhaustion of Lulism to the rise of Bolsonarism, showing how elite economic interests have been rearticulated through new forms of digital ideological production. By foregrounding the cultural work of Brazil's far-right influencers, the article highlights how neo-liberalism is able to renew itself through its crises. The findings speak to broader trends in contemporary capitalism, offering insight into how far-right media ecosystems help to (re)forge hegemonic stability across other liberal democracies facing similar political circumstances.

Abstract This article addresses the underexplored dynamics of artificial intelligence (AI) technology transfer by the United States/China to the global South, and the implications for the technological advancement of the latter. While previous research has examined general patterns of AI exchange and their geopolitical implications, few studies have provided a systematic comparative analysis of the modes of AI technology transfer and their concrete effects on recipient countries in the global South. This article addresses that gap by introducing a typology that distinguishes the US as exemplifying a ‘leader’ mode characterized by a high ‘systematicity of transfer’ and low ‘preparedness for localization’, and China as exemplifying a ‘collaborator’ mode characterized by a low ‘systematicity of transfer’ and high ‘preparedness for localization’. Building on this typology, the article analyses how these divergent transfer modes shape the global South's AI capabilities, development trajectories and AI regulatory frameworks. The US' ‘leader’ mode offers coherent and governance-oriented AI systems but risks creating vertical dependency and limited local absorption, whereas China's ‘collaborator’ mode facilitates cost-effective adoption and local capacity-building, but often lacks robust regulatory frameworks and comprehensive integration. This article provides a framework for future research on digital sovereignty and for the efforts of policy-makers in the global South to design AI strategies that balance developmental gains with long-term autonomy.