ACADEMIC INTEGRITY IN THE CONTEXT OF THE USE OF BIG DATA AND ARTIFICIAL INTELLIGENCE IN SCIENTIFIC RESEARCH: ETHICAL RISKS

Abstract

The rapid development of Big Data and Artificial Intelligence (AI) technologies has transformed the landscape of scientific research, offering unprecedented opportunities for data analysis, modeling, and discovery. However, these advancements also introduce significant ethical challenges that directly impact academic integrity. This paper explores the key issues related to the ethical use of Big Data and AI in research, emphasizing the principles of honesty, transparency, responsibility, and accountability. Major challenges identified include the potential biases inherent in datasets and algorithms, the opacity of AI models, risks of plagiarism or misrepresentation of results, and the threat to participants’ privacy. The paper analyzes how these risks can compromise the reliability and credibility of scientific findings if not properly addressed. By integrating ethical considerations into the design, implementation, and dissemination of AI-based research, the scientific community can maximize the benefits of technological advancements while maintaining the trustworthiness of scholarly work. This paper contributes to the ongoing discussion on responsible AI in science and provides a methodological basis for fostering academic integrity in the era of digital research.