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OGERIA — Observatory of Global Evidence on Risks in AISynthesis report · 2026 ed.
Updated 2 Oct 2026

Chapter 01 · Risk map

A state that stops funding itself by taxing its population's labour loses the material reason to invest in it.

Severity
Irreversible
Horizon
3–10 years
Evidence
Projected
Consensus
Low

The argument is not about technology but about the incentives of those in charge. A state that funds its spending by taxing the labour of its population has a material —not moral— reason for that population to be healthy, educated and productive: it is its tax base. A rentier state, which draws its income from a resource, does not. Luke Drago and Rudolf Laine transfer the resource-curse literature to AI: with AI capable of substituting for labour, powerful actors lose the incentive to invest in ordinary people [336]The Intelligence CurseDrago, Luke; Laine, Rudolf · 2025 · reportView source ↗Accessed on 9 September 2026. They open with the Democratic Republic of the Congo: more than 24 trillion dollars in untapped minerals and 73.5% of the population below 2.15 dollars a day in 2024.

The empirical step the argument needs is for income to shift from labour to capital. The International AI Safety Report 2026 puts it in the conditional: AI adoption may shift income from labour towards owners of capital [538]International AI Safety Report 2026Bengio, Yoshua · 2026 · reportView source ↗Accessed on 9 September 2026.

What this does not demonstrate. The resource curse is not deterministic, and the authors themselves cite the evidence that contradicts them: with comparable per capita rents and long-standing autocrats, infant mortality in Oman fell from 159 per thousand in 1971 to 9 in 2010, while in Equatorial Guinea it went from 263 to 109 over the same period [336]The Intelligence CurseDrago, Luke; Laine, Rudolf · 2025 · reportView source ↗Accessed on 9 September 2026. Pyramid-shaped replacement from the bottom upwards is an extrapolated prediction, and the fact that its first rung coincides with youth hiring data does not validate the whole chain. And the series that would have to break has not broken: labour’s share of US GDP has stayed around 60% for more than a century [618]Gradual Disempowerment: Systemic Existential Risks from Incremental AI DevelopmentKulveit, Jan; Douglas, Raymond; Ammann, Nora et al. · 2025 · paperView source ↗Accessed on 9 September 2026. In Denmark the effect on earnings and hours is a precise null that rules out effects larger than 2% [535]Still Waters, Rapid Currents: Early Labor Market Transformation under Generative AIHumlum, Anders; Vestergaard, Emilie · 2026 · preprintView source ↗Accessed on 9 September 2026.

Chain of materialisation

  1. PreconditionObserved

    The modern state funds itself by taxing labour

    The US labour share of GDP has stayed near 60% for over a century, and that stability is the tax base on which the welfare state was built. A state that taxes labour has a material reason for its population to be healthy, educated and productive.

    Observed and demonstrated evidence ends here. What follows is projection.

  2. TriggerProjected

    Income shifts towards capital owners

    The international report states the point cautiously: AI adoption may shift earnings from labour to capital owners, such as shareholders of firms that develop or use AI. It is model-based projection, not an observed series breaking.

  3. CascadeProjected

    Rentier logic replaces contributory logic

    Drago and Laine transpose the resource curse: a state that draws income from a resource invests only as much as it takes to get the resource out of the ground and to the port. Their opening example is the Democratic Republic of the Congo, with over 24 trillion dollars in untapped minerals and 73.5% of its population under 2.15 dollars a day in 2024.

  4. ImpactSpeculative

    With no money, people lose their leverage to demand

    The final step of the argument is political, not economic, and its own authors write it as such. There is no measurement of any kind, and the historical analogy that supports it admits counterexamples.

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Sources

  1. [336] The Intelligence Curse · Drago, Luke 2025
  2. [618] Gradual Disempowerment: Systemic Existential Risks from Incremental AI Development · Kulveit, Jan 2025
  3. [15] The Simple Macroeconomics of AI · MIT / NBER 2025
  4. [538] International AI Safety Report 2026 · International AI Safety Report (panel con representantes nominados por más de 30 países) 2026
  5. [550] Gen-AI: Artificial Intelligence and the Future of Work · Fondo Monetario Internacional 2024 archived copy only
  6. [773] AI as Normal Technology · Knight First Amendment Institute at Columbia University 2025
  7. [535] Still Waters, Rapid Currents: Early Labor Market Transformation under Generative AI · NBER / University of Chicago 2026

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