SCIENTIFIC RESEARCH AND ADHERENCE TO ACADEMIC INTEGRITY IN THE CONTEXT OF ARTIFICIAL INTELLIGENCE DEVELOPMENT

Abstract

The article explores the evolutionary relationship between the development of science and human intellect, emphasizing science as a social institution, a form of organized activity, and a structured system of knowledge. Particular attention is paid to the rapid integration of artificial intelligence (AI) technologies into scientific research and higher education, which fundamentally transforms traditional research practices, analytical processes, and educational methodologies. In this context, academic integrity is identified as a crucial condition for ensuring the reliability, transparency, and ethical validity of scientific and educational outcomes.

The study highlights that artificial intelligence provides substantial advantages, including accelerated data processing, advanced analytical capabilities, modeling, forecasting, and the automation of routine research tasks. At the same time, the widespread use of generative and multimodal AI systems introduces significant risks related to academic misconduct, loss of originality, authorship ambiguity, algorithmic bias, and the dissemination of unreliable or insufficiently verified results. These challenges intensify the need for clear ethical standards, legal regulation, and institutional policies governing the use of AI in academic environments.

The article analyzes key stages in the evolution of science and artificial intelligence, demonstrating that AI represents a logical continuation of post-non-classical scientific development, where information and cognitive processes become central research paradigms. Definitions of core concepts such as artificial intelligence, neural networks, AI systems, and chatbots are systematized in accordance with current legislation and academic discourse. The dual impact of AI on both educators and students is examined, outlining its positive contributions to personalization of learning and research efficiency, alongside its potential negative consequences for critical thinking and academic culture.

The authors conclude that maintaining high ethical standards in contemporary digital science requires the responsible, transparent, and critically reflective use of artificial intelligence tools, combined with strict adherence to the principles of academic integrity. The article substantiates the necessity of developing regulatory mechanisms and institutional guidelines that balance technological innovation with the preservation of trust, originality, and credibility in scientific research and education.