Governing Artificial Intelligence as a Macro Socio-Technical Regime: The F-I-C-P Framework for Regime-Level AI Infrastructure and Governance

arXiv:2610.32985v1 Announce Type: new Abstract: Artificial intelligence (AI) is often analysed through technical, organisational, or regulatory perspectives that treat capability, adoption, and governance as separate issues. This article conceptualises AI instead as an emerging macro socio-technical regime generated through the interaction of finance, infrastructure, capability, and productivity. It develops the F-I-C-P framework to explain how finance enables infrastructure, infrastructure conditions capability, and capability creates the possibility--but not the guarantee--of productivity and value realisation. The article also introduces the concept of regime-level AI infrastructure to identify concrete configurations, such as AI Gigafactories, foundation-model platforms, national compute infrastructures, public AI platforms, sectoral AI ecosystems, and corporate AI infrastructures, through which the macro-regime becomes observable and evaluable. The central analytical problem is structural misalignment: the risk that financial expectations, infrastructural expansion, technical capability, organisational absorption, productivity realisation, governance capacity, and societal outcomes evolve at different speeds or under unequal conditions of power. Governance is therefore conceptualised not as a final stage after technological deployment, but as a transversal and anticipatory steering capacity. Briefly illustrated through Spain and Chile as non-frontier configurations, the article argues that AI governance should be understood as regime alignment: the task of anticipating

The article presents a framework for understanding AI governance, but does not make a substantive claim about AI's effect on society.

The article presents a conceptual framework (F-I-C-P) aiming to improve understanding of AI governance by addressing structural misalignments in finance, infrastructure, capability, and productivity. This anticipatory governance could mitigate risks but also reveals complex challenges that could cause uneven societal outcomes, implying both opportunity and concern.

This is a theoretical governance framework paper, not an empirical finding about AI's societal effects. It proposes concepts for analyzing risk but makes no concrete claims about outcomes, so the implication for human flourishing is essentially undetermined here.

This academic paper proposes a framework for understanding and governing AI as a 'macro socio-technical regime.' It highlights the risk of structural misalignment between finance, infrastructure, capability, productivity, and governance, which could lead to negative societal outcomes. The article itself is theoretical, presenting a conceptual framework and not empirical findings or observed impacts.

SOURCE     arXiv cs.CY (Computers and Society) (tier 1)
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DOCUMENT   4962b64a-74a7-4a85-9f76-7246b1109abc
           https://arxiv.org/abs/2610.32985
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EVIDENCE   0 extracted excerpts
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MODEL RUN  4 runs, methodology 1.0.1
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SCORE      -40  (Adverse)
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CONFIDENCE 48%