‘Ethics’ and ‘Integrity’ in Research in the Era of Generative AI—Are We Ready to Contribute to Scientific Inquiries?

Abstract

As scientific research advances, the tools used by researchers to conduct and publish their studies are also evolving in both academic and non-academic settings. Research serves as the foundation of knowledge production, but recent advancements in generative AI have raised concerns about the strength and quality of research (Dahal, 2024). These concerns hinge on two key factors: research ethics and research integrity. In scientific research, ethics and integrity are essential for credible studies. Research ethics involve moral principles such as informed consent and confidentiality, while research integrity focuses on honesty and transparency. These principles reinforce one another, fostering trust within the scientific community. Upholding these standards requires a collective effort to ensure reliable scientific research. In this editorial, I argue that while ethics and integrity are closely interconnected, they are not synonymous. Instead, they work together to uphold scientific inquiries' credibility, transparency, and impact. Furthermore, this editorial emphasizes the broader role of ethics and integrity in strengthening scholarly work rather than simply linking them to research quality. Finally, it concludes with a brief overview of the articles featured in Volume 2, Issue 1.