Можливості та виклики мовних моделей штучного інтелекту у вищій освіті для сталого розвитку

At the same This article examines the contemporary opportunities and limitations of using large language models (LLMs), including ChatGPT, in higher education and scientific research. It outlines the technological foundations of LLMs, highlighting their capabilities for context-aware dialogue, language synthesis, automated assessment, and personalization of learning pathways, including applications in language learningand intercultural communication that can support learner autonomy and communicative competence. The study emphasizes the potential of AI to enhance the quality of education, support pedagogical decision-making, and improve the management of educational processes. At the same time, key risks are identified, including informational biases, reliance on training data, the potential generation of inaccurate content, threats to privacy, and challenges to academic integrity. Ethical considerations are discussed, focusing on algorithmic transparency, data security, researcher accountability, and the prevention of discriminatory effects. The article also presents key strategies for addressing these challenges, including the development of information and ethical literacy, the establishment of transparent university policies, clarification of scientific publication requirements, and implementation of guidelines for responsible LLM use. The study concludes that effective integration of LLMs into academic environments requires a balanced combination of innovative potential and ethical safeguards to ensure the integrity of education and scientific research.