Harnessing Artificial Intelligence in Stock Market Investments: A Neomarxist Approach to Alternative Socioeconomic Funding Agendas for National State Revenue Accumulation
In the contemporary economic, sociological and political landscape, the successful integration of Artificial Intelligence (AI) computer programs into the predicted behaviour of stock market value in the financial markets represents a profound burgeoning frontier in economics, with profound implications for both wealth generation and national budget resource allocation. This paper explores the potential sociopolitical economic strategy of using AI-driven stock market prediction predictions to cumulatively accumulate capital funded for by taxpayer sourced representative income. As the baseline return accumulates in the form of investment potential then as a means of revenue accumulation for the state then the burden of the national budget upon its citizens decreases then ceases. This is the theorisation of the establishment of a Marxist economic social superstructure for the funding of social institutions through the powerful potential of artificial intelligence. By leveraging a portion of the national budget on advanced AI technologies, this strategy could dramatically facilitate the financial sustenance of political budgets aimed at social equity and economic justice. Through a critical review of sociological and economic theories, this theoretical research delineates exactly how such an approach could potentially reconfigure the mode of production and contribute to the reformation of a sustainable socialist economy.
Authors
- Suraj Gowda (ORCID: https://orcid.org/0000-0002-1580-1367)
- Alan Peter Garfoot
Publication Details
- Journal
- Economics Politics and Regional Development
- Published
- 2024-11-06
- DOI
- https://doi.org/10.22158/eprd.v5n2p60
- Primary Topic
- Financial Literacy, Pension, Retirement Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00