An AI Capability Threshold for Rent-Funded Universal Basic Income in an AI-Automated Economy

• URL: http://arxiv.org/abs/2505.18687v2
• Date: Sat, 26 Jul 2025 14:29:30 GMT
• Title: An AI Capability Threshold for Rent-Funded Universal Basic Income in an AI-Automated Economy
• Authors: Aran Nayebi,
• Abstract summary: We derive the first closed-form condition under which AI capital profits could sustainably finance a universal basic income.<n>We analyze how the AI capability threshold--defined as the productivity level of AI relative to pre-AI automation--varies under different economic scenarios.
• Score: 2.6451153531057985
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We derive the first closed-form condition under which artificial intelligence (AI) capital profits could sustainably finance a universal basic income (UBI) without additional taxes or new job creation. In a Solow-Zeira economy characterized by a continuum of automatable tasks, a constant net saving rate $s$, and task-elasticity $\sigma < 1$, we analyze how the AI capability threshold--defined as the productivity level of AI relative to pre-AI automation--varies under different economic scenarios. At present economic parameters, we find that AI systems must achieve only approximately 5-6 times existing automation productivity to finance an 11%-of-GDP UBI, in the worst case situation where *no* new jobs or tasks are created. Our analysis also reveals some specific policy levers: raising public revenue share (e.g. profit taxation) of AI capital from the current 15% to about 33% halves the required AI capability threshold to attain UBI to 3 times existing automotion productivity, but gains diminish beyond 50% public revenue share, especially if regulatory costs increase. Market structure also strongly affects outcomes: monopolistic or concentrated oligopolistic markets reduce the threshold by increasing economic rents, whereas heightened competition significantly raises it. Overall, these results suggest a couple policy recommendations: maximizing public revenue share up to a point so that operating costs are minimized, and strategically managing market competition can ensure AI's growing capabilities translate into meaningful social benefits within realistic technological progress scenarios.

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