Navigating ethical challenges in generative AI-enhanced research: The ETHICAL framework for responsible generative AI use
Article
Article Title | Navigating ethical challenges in generative AI-enhanced research: The ETHICAL framework for responsible generative AI use |
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ERA Journal ID | 213114 |
Article Category | Article |
Authors | Roux, Rian, Eacersall, Douglas, Pretorius, Lynette, Smirnov, Ivan, Spray, Erika, Illingworth, Sam, Chugh, Ritesh, Strydom, Sonja, Stratton-Maher, Dianne, Simmons, Jonathan, Jenning, Isaac, Kamrowski, Ruth, Downie, Abigail, Thong, Chee Ling and Howell, Katharine A. |
Journal Title | Journal of Applied Learning and Teaching |
Journal Citation | 8 (2), pp. 1-14 |
Number of Pages | 14 |
Year | 2025 |
Publisher | Kaplan Higher Education Academy |
Place of Publication | Singapore |
ISSN | 2591-801X |
Digital Object Identifier (DOI) | https://doi.org/10.37074/jalt.2025.8.2.9 |
Web Address (URL) | https://journals.sfu.ca/jalt/index.php/jalt/article/view/3079 |
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. |
Keywords | Applied Artificial Intelligence; Generative AI; ChatGPT; Ethics; Research integrity; AI-enhanced research |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 399999. Other education not elsewhere classified |
460299. Artificial intelligence not elsewhere classified | |
Byline Affiliations | Library Services |
Monash University | |
University of Technology Sydney | |
University of Newcastle | |
Edinburgh Napier University, Untied States | |
Central Queensland University | |
Stellenbosch University, South Africa | |
School of Nursing and Midwifery | |
University of Alberta, Canada | |
Griffith University | |
UniSQ College | |
UCSI University, Malaysia | |
Edith Cowan University |
https://research.usq.edu.au/item/zwx72/navigating-ethical-challenges-in-generative-ai-enhanced-research-the-ethical-framework-for-responsible-generative-ai-use
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3079-Article Text-9825-3-10-20250722.pdf | ||
License: CC BY 4.0 | ||
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