Gauging Growth: AGI Mathematical Metrics for Economic Progress

Paper: arXiv 2506.03156

Authors: Davit Gondauri

Abstract

Today, the economy is greatly influenced by Artificial General Intelligence (AGI). The purpose of this paper is to determine the impact of the quantitative relations of AGI on the country’s economic parameters. The authors use the analysis of historical data in the research, develop a new mathematical algorithm that refers to the level of AGI development, and conduct a regression analysis. The economic effect of AGI is deduced if it affects the growth of real GDP. As a result of the analysis, it is revealed that there is a positive Pearson correlation between the growth of AGI and real GDP; that is, to increase GDP by 1%, an average increase of 12.5% of AGI is required.

Complexity vs Empirical Score

• Math Complexity: 3.5/10
• Empirical Rigor: 2.5/10
• Quadrant: Philosophers — conceptual discussion, limited math and data

Why this score: The paper attempts to model the economic impact of AGI using a modified Cobb-Douglas production function, but its operationalization of ‘AGI level’ is tautological—simply rearranging the production function to isolate a residual parameter. Furthermore, it lacks rigorous statistical validation, dataset specifics, and clear reproducible implementation details.

Research Flowchart

  flowchart TD
    A[Research Goal: Assess AGI's Impact on Real GDP Growth] --> B[Data Input: Historical Economic & AGI Development Data]
    B --> C[Methodology: Develop Mathematical Algorithm for AGI Level]
    C --> D[Analysis: Regression Analysis & Pearson Correlation]
    D --> E[Outcome: Positive Correlation Between AGI & GDP]
    E --> F[Key Finding: 12.5% AGI Growth Yields 1% Real GDP Increase]