Artificial intelligence, generative artificial intelligence and research integrity: a hybrid systemic review

Abstract

Abstract Current advances in academic research stem from two main sources: artificial intelligence technologies and the specific field of generative artificial intelligence. However, the ethical use of these technologies and their implications for academic integrity has not been sufficiently investigated. Therefore, this research examines the ethical use of artificial intelligence technologies and Generative Artificial Intelligence in academic research. It focuses on the current field conditions, detection of research trends, and critical gaps. The study uses a combination of bibliometric and thematic content analysis methods to examine the methodological framework of AI, GenAI, and academic integrity from an interdisciplinary perspective. The research reveals that GenAI integration speed has accelerated across all research stages, including academic writing, literature review, data analysis, and hypothesis development. The study also identifies risks such as biased algorithms, plagiarism risk, false information production, and potential damage to academic integrity. The research ethics approaches developed by academic institutions and journals have not reached maturity in the context of AI. Future research on GenAI within academic processes requires forming ethical principles integrated with oversight systems and policy frameworks.

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