TRANSFORMATION OF SOCIAL AND EDUCATIONAL SYSTEMS UNDER THE INFLUENCE OF ARTIFICIAL INTELLIGENCE
Abstract
Relevance. Over the past decade, artificial intelligence (AI) has emerged as a key driver of global socio-economic change, integrating into industry, healthcare, and education at an unprecedented pace. Despite this technological expansion, a significant gap persists between students’ interest in intelligent systems and their actual understanding of the complexity of professional pathways in this field. Existing theoretical gaps concern model interpretability and the ethical use of algorithms, while practical challenges relate to labor market transformation and the risks of job displacement due to automation.
Purpose. The study aims to provide a comprehensive analysis of the current state and practical implementation of AI systems in social and educational environments, as well as to verify the functional capabilities of next-generation language models as tools for supporting professional activities and decision-making.
Methods. The methodology is based on a combination of theoretical analysis of scholarly sources and experimental modeling. The research design included: a critical review of interdisciplinary publications; case studies of generative systems (ChatGPT, Bard) using prompt engineering principles; mathematical modeling of linear programming problems in the R programming environment using the lpSolve package; and comparative verification of results.
Results. It was established that modern language models are capable of generating coherent research strategies, acting as intellectual navigators. A practical experiment involving the solution of optimization problems confirmed the ability of AI to accurately transform mathematical descriptions into program code, yielding optimal solutions (in particular, values of X1 = 3.33 and X2 = 1.33 were obtained for the resource model). Comparative analysis revealed the advantages of ChatGPT in maintaining conversational context and Google Bard in handling up-to-date data. At the same time, the phenomenon of “apparent correctness” (AI hallucinations) was identified, along with social risks such as BT Group’s plans to reduce 55,000 jobs by 2030 due to automation. Conversely, the implementation of systems such as Surtrac has reduced waiting times in urban traffic congestion by up to 40%.
Conclusions. It is demonstrated that AI functions as an effective enhancer of intellectual activity rather than a replacement for human cognition. The significance of the findings lies in substantiating the need to adapt educational programs to interdisciplinary requirements that integrate cognitive sciences and programming. The practical application of AI requires mandatory expert verification of results and the preservation of users’ critical thinking to prevent factual errors.
Keywords
generative models, labor market transformation, prompt engineering, linear programming, digital competence.
Author Biography
Wladyslaw Wornalkewicz
Doctor of Engineering, Professor ANS-WSZiA, Academy of Applied Sciences – Higher School of Management and Administration in Opole (Poland) https://orcid.org/0009-0007-2241-262X
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