ARTIFICIAL INTELLIGENCE AND UZBEK LANGUAGE

258 ARTIFICIAL INTELLIGENCE AND UZBEK LANGUAGE Mirzayeva Sevinch UzSWLU, 3rd Faculty, Group 2211 Scientific supervisor: A.Shofqorov DOI: https://doi.org/10.5281/zenodo.17450690 Abstract: Artificial Intelligence (AI) is rapidly transforming the ways in which languages are taught, studied, and preserved. For the Uzbek language, AI presents both a challenge and an opportunity: it offers new tools for education and communication while simultaneously creating risks for authenticity and linguistic purity. This paper argues that the increasing use of AI, particularly Large Language Models (LLMs), requires educational reforms in three main directions — assessment, teaching methodology, and technological diagnostics. By reforming evaluation systems, innovating pedagogical methods, and developing AI-detection technologies, Uzbekistan can integrate AI responsibly while safeguarding the intellectual independence of its students and the cultural identity of its national language. Keywords: Artificial intelligence, Uzbek language, education reform, assessment, methodology, LLMs, academic integrity, technology. Introduction The rapid development of Artificial Intelligence has changed the structure of global communication, language education, and creative production. With tools like ChatGPT and other LLMs, students can generate complex academic texts in seconds. This has raised fundamental questions for educators: What does originality mean in the age of AI? How can we measure a student’s independent thinking when technology can generate entire essays? For the Uzbek language, this issue is especially critical. As a morphologically rich and culturally expressive language, Uzbek carries deep historical identity. However, the overuse of AI tools without pedagogical regulation may lead to linguistic simplification, translation errors, and the erosion of authentic student voice. Therefore, the goal of this research is to analyze the relationship between AI and Uzbek language education and propose scientifically grounded solutions in three main directions: reforming assessment criteria, improving teaching methodology, and creating technological diagnostics for detecting AI-generated content. 1. Reforming Assessment Criteria Traditional assessment systems in Uzbekistan focus primarily on final written products. With the introduction of LLMs, students can now produce fluent, error-free essays that do not reflect their real thinking or linguistic skills. To solve this, the assessment process must move from product-based to process-based evaluation, emphasizing originality, reasoning, and progress over time. 259 Proposed Reforms: 1. Process Assessment – Evaluate outlines, drafts, bibliographies, and reflective comments as separate stages. 2. Oral Defenses – Require students to explain their work orally. 3. Rubric-Based Grading – Use rubrics that value originality and independent thought. 4. Authentic Tasks – Design assignments AI cannot easily generate. 5. AI Literacy Education – Teach students ethical AI usage. Expected Outcomes: Reduced plagiarism, improved thinking, and creativitybased evaluation. 2. Improving Teaching Methodology Many Uzbek language classes still rely on memorization. In an AI-driven world, this is ineffective because LLMs already possess vast factual knowledge. The aim is to transform Uzbek language education to develop critical, creative, and analytical thinking. Key Proposals: 1. Shift from Knowledge to Skills. 2. Project-Based Learning. 3. Collaborative AI Use. 4. Interdisciplinary Approach. 5. Teacher Training. Expected Outcomes: Learners become more critical and creative; teachers adapt confidently to AI-assisted learning environments. 3. Developing Technological Diagnostics AI can generate texts indistinguishable from human writing, which makes plagiarism detection difficult. Uzbekistan lacks language-specific AI detectors. The solution is to develop diagnostic technologies tailored to the Uzbek language. Proposed Solutions: 1. National AI Detection Systems. 2. Integration with University Platforms. 3. Cross-Linguistic Calibration. 4. Continuous Data Updates. 5. Transparency and Ethics. Expected Outcomes: Reliable AI detection, stronger academic honesty, and improved digital sovereignty in education. Conclusion 260 Artificial Intelligence is not an enemy of education; it is a powerful tool that must be guided with ethical and intellectual discipline. For the Uzbek language, AI represents both modernization and preservation. Reforming assessment systems, modernizing teaching methodology, and developing technological diagnostics are essential steps toward building a balanced educational model where AI supports — rather than replaces — human intelligence. In the future, Uzbekistan can become a regional leader in ethical AI integration, ensuring that its national language thrives in the digital century. References 1. Karimov, A. (2023). Artificial Intelligence and National Languages: The Case of Uzbek. Tashkent State Technical University Press. 2. Rakhmatova, S. (2022). Natural Language Processing for Agglutinative Languages. Uzbek Journal of Linguistics, 4(2), 55–68. 3. Nurmatov, D. (2021). Digital Linguistics and Uzbek Language Development. Uzbek Academy of Sciences. 4. Jurayev, M. (2020). Speech Technologies in Central Asian Languages. IEEE Conference Proceedings, 22(3), 199–210. 5. Kaplan, J. (2023). Artificial Intelligence: What Everyone Needs to Know. Oxford University Press. 6. Floridi, L. (2021). 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