Navigating ethical challenges in generative AI-enhanced research: The ETHICAL framework for responsible generative AI use

Authors/Creators

Douglas Eacersall
Lynette Pretorius
Ivan Smirnov
Erika Spray
Sam Illingworth
Ritesh Chugh
Sonja Strydom
Dianne Stratton-Maher
Jonathan Simmons
Isaac Jennings
Rian Roux
Ruth Kamrowski
Abigail Downie
Chee Ling Thong
Katharine A. Howell, Edith Cowan UniversityFollow

Abstract

The rapid adoption of generative artificial intelligence (GenAI) in research presents both opportunities and ethical challenges that should be carefully navigated. Although GenAI tools can enhance research efficiency by automating tasks such as literature reviews and data analysis, their use raises concerns about aspects including data accuracy, privacy, bias, and research integrity. This paper proposes the ETHICAL framework, which is a practical guide for responsible GenAI use in research. Employing a multi-stage single case study design, we examine multiple GenAI tools in real research contexts to develop the ETHICAL framework, which consists of seven key principles: Examine policies and guidelines, Think about social impacts, Harness understanding of the technology, Indicate use, Critically engage with outputs, Access secure versions, and Look at user agreements. Applying these principles will enable researchers to uphold research integrity while leveraging the benefits of GenAI. The framework addresses a critical gap between awareness of ethical issues and practical action steps, providing researchers with concrete guidance for ethical GenAI integration. This work has implications for research practice, institutional policy development, and the broader academic community as researchers adapt to an AI-enhanced research landscape. The ETHICAL framework can also serve as a foundation for developing AI literacy in academia and promoting responsible GenAI adoption in research settings.

Document Type

Journal Article

Date of Publication

7-22-2025

Volume

8

Issue

2

Publication Title

Journal of Applied Learning and Teaching

Publisher

Kaplan Singapore

School

Graduate Research School

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.

Comments

Eacersall, D., Pretorius, L., Smirnov, I., Spray, E., Illingworth, S., Chugh, R., Strydom, S., Stratton-Maher, D., Simmons, J., Jennings, I., Roux, R., Kamrowski, R., Downie, A., Thong, C. L., & Howell, K. A. (2025). Navigating ethical challenges in generative AI-enhanced research: The ETHICAL framework for responsible generative AI use. Journal of Applied Learning & Teaching, 8(2). https://doi.org/10.37074/jalt.2025.8.2.9

First Page

102

Last Page

115