Ethical Dimensions of Artificial Intelligence in Scientific Research: a Case Study of «7m01504 – Chemistry» Master's Program

Abstract

This article examines the ethical challenges and practical implications of integrating Generative Artificial Intelligence (AI) into academic research and thesis writing. As AI tools become deeply embedded in higher education, the distinction between legitimate research support and academic dishonesty has become a critical concern. This study provides a comprehensive analysis of ethical risks, such as "ghost-authoring" and "AI hallucinations," while emphasizing the necessity of maintaining academic integrity. A central component of this research is an empirical survey conducted among first-year master’s students of the "7M01504 – Chemistry" educational program at K. Zhubanov Aktobe Regional University. The results indicate that while 75% of students use AI for technical tasks, they frequently encounter the "False Positive" phenomenon—where original, human-written scientific content is incorrectly flagged as machine-generated by detection software. The paper proposes a strategic framework for the ethical use of AI, including the implementation of a "Disclosure Protocol" and a shift from algorithmic surveillance to substantive mentoring. It reviews international guidelines from COPE and UNESCO to advocate for a "Human-in-the-Loop" approach. The study concludes that fostering a culture of digital responsibility and transparency is essential for protecting the reputation of researchers and academic institutions in the AI era.