Ideology, Digital Economy and Prompt-Knowledge

The article examines the influence of ideology on economic science in the context of digitalization and artificial intelligence (AI) development, based on the interpretation of ideology within the scientific tradition of Douglass North and Joseph Schumpeter. In North’s framework, ideology is understood as a set of mental models shaping the perception and interpretation of economic phenomena. In Schumpeterian logic, the emphasis is on the inevitability of ideological influence in science through pre-scientific cognitive acts that form the research framework. The study demonstrates that automation of scientific procedures using AI enhances the impact of ideological attitudes on the process of cognition. The article identifies five key ideological trends in Russian economic science (neoliberalism, dirigisme, socialism, special path, and environmentalism) using machine learning methods. The results indicate the dominance of dirigisme, which is explained by historical and institutional factors. Digital transformation, by boosting mechanisms of increasing returns, not only alters data processing methods but also creates new meanings, amplifying the role of ideology in economic and political sustainability. The article focuses on neoliberal ideology, which, in the digital economy, manifests through algorithmization, technocratic optimization, and the promotion of market efficiency. Neoliberalism dominates global discourse and promotes marketization even in the public sector, leading to an increasing dependence on metrics and indicators. This, in turn, leads to excessive bureaucratization and a focus on short-term goals. Special attention is given to the concept of prompt-knowledge, which emerges from human-AI interaction, where excessive AI use can lead to a shallow understanding of knowledge and reduced motivation for creative activity.