Artificial Intelligence in Teaching Macroeconomics: Opportunities, Risks, and Practical Implications for Higher Education in Uzbekistan

This working paper examines the role of artificial intelligence, particularly generative AI, in teaching macroeconomics in higher education, with specific attention to Uzbekistan. It discusses the opportunities of AI-supported explanation, visualization, personalized feedback, assessment design, data interpretation, and case-based learning, while also addressing risks related to academic integrity, inaccurate outputs, overreliance on automated tools, privacy, bias, and unequal access. The paper proposes a teacher-centered framework based on pedagogical purpose, human verification, transparency, academic integrity, contextual relevance, and inclusive access. The study is intended as a conceptual and policy-oriented contribution for educators, researchers, and higher education institutions adapting to the digital transformation of teaching and learning.

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