Integrating Ethics and Governance in Research in the Era of Artificial Intelligence

Abstract

This academic article aims to propose a framework for integrating ethics and governance into the research process in the era of artificial intelligence (AI). Amidst the rapid evolution of generative AI technology, research integrity standards face unprecedented challenges. The analysis reveals that contemporary ethical issues extend beyond traditional plagiarism to encompass new forms of research misconduct, including AI-driven data fabrication, algorithmic falsification, and synthetic plagiarism. This article proposes a Research Life Cycle Governance framework focusing on three critical phases: literature review, data analysis, and publication. The framework emphasizes transparency through mandatory disclosure and adherence to data privacy regulations (PDPA). The conclusion highlights the indispensable "human-in-the-loop" principle, asserting that ultimate accountability remains with researchers and advisors and cannot be transferred to technology. Finally, the article provides policy recommendations for academic institutions to cultivate an AI-literate research ecosystem to uphold international academic standards.