The Ethical Protocol for Responsible Use of Generative AI for Research Purposes in Higher Education

Abstract

Generative AI’s growing use in higher education research requires strong pro-tocols for responsible use. This need arises from the potential for misuse andthe current uncertainty around ethical concerns and intellectual property. Thelack of clear rules about openness in AI use, along with the “black box” natureof many AI systems, raises worries about reproducibility and the possibility ofbiased or fake results. This paper focuses specifically on generative AI tools(e.g., LLMs like ChatGPT, research-specific platforms like Elicit/SciSpace). Thepaper presents the ETHICAL protocol (i.e., Establish your purpose, Thoroughlyexplore options, Harness the appropriate tool, Inspect and verify output, Citeand reference accurately, Acknowledge AI usage transparently, and Look overpublisher’s guidelines), a detailed guide designed to direct researchers in the eth-ical and responsible inclusion of generative AI in their work. The protocol wascreated through a multi-step process, including a scientometric review of cur-rent trends, a systematic review of researcher experiences, and a policy analysisof 74 documents from various stakeholders (authorities, universities, publishers,and publication manuals). This analysis shaped the creation of a seven-heading,nine-item checklist covering key aspects of responsible AI use, from setting clearresearch goals to checking outputs and openly acknowledging AI help. The ETH-ICAL protocol gives practical examples and detailed explanations for each item,highlighting the importance of AI literacy and careful choice of suitable tools. Italso stresses the vital need for checking AI-generated content to lessen the riskof errors and made-up information (“hallucinations”). The resulting protocoloffers a practical and easy-to-use guide for researchers, encouraging responsibleAI practices and upholding academic integrity. The ETHICAL protocol offers ahelpful tool for managing the complex area of AI in research, ultimately leadingto more open, reliable, and ethically sound scholarly work. Its broad acceptancecould greatly improve the responsible use of AI in higher education, buildingtrust and furthering knowledge growth