Ethical Challenges in the Era of Generative AI: Insights from a Practice-Informed Rapid Review

This study investigates the integration of Generative AI (GenAI) into academic research, highlighting both its transformative potential and the ethical, methodological, and epistemological challenges it introduces. While GenAI enhances efficiency in tasks like text generation, data analysis, and translation, it raises serious concerns around authorship, originality, transparency, data privacy, and accountability. Through a rapid review of literature from 2022 to 2025, guided by the European Code of Conduct for Research Integrity, the study identifies recurring risks such as algorithmic bias, fabricated citations, and diminished scholarly authorship. In response, it proposes a five-principle ethical framework—human oversight, accuracy, accountability, data protection, and institutional governance—and emphasizes that responsible GenAI use requires not only technical safeguards but also ethical literacy, critical reflection, and transparent disclosure. Ultimately, GenAI should serve as a collaborative partner that augments human creativity while preserving the integrity and rigor of scientific inquiry.

Generative Artificial Intelligence, research ethics

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