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To AI or not to AI: A cross-sectional analysis of artificial intelligence policy among emergency management journals
Amidu Kalokoh1, Issa B Thullah2, Hans Louis-Charles2
1Virginia Commonwealth University, Richmond, Virginia. ORCID: https://orcid.org/0000-0002-2952-1489.
Abstract:
Artificial intelligence (AI) continues to transform our society, with direct impacts on the field of emergency management. As AI becomes increasingly integrated into educational institutions, scholars have expressed concerns regarding the ethical and educational implications of AI usage in higher education. This impact and use of AI will have tremendous implications for the scholarship of teaching and learning and the core competencies of the emergency management profession. This study argues that, within the discipline of emergency management, a lesser-used but valuable metric for academic AI guidance can be found in the policies of the most revered journal publications in the field. This study provides a snapshot of how journal publications in emergency management currently approach AI usage with regard to authorship, peer review, and the editorial process. This study presents a cross-sectional analysis of 108 emergency management journals across multiple databases, identifying 71 journals with publicly available AI guidelines for authors, reviewers, or editors. For potential authors, our qualitative thematic findings reveal consensus support for AI use in proofreading and moderate support for use in statistical analysis. There is moderate support for the use of generative AI/large language models (LLMs) in passage creation, and low support for image/figure creation; however, both require full disclosure and accountability when used. There was a unanimous stance against granting authorship or coauthorship to AI. Guidelines for reviewers show strong opposition against using AI, especially LLMs, due to confidentiality and privacy concerns. Likewise, editors are mostly banned from using LLMs, unless they are used only for identifying potential reviewers or provided with an in-house publisher-owned AI tool. Our study concludes with a discussion on the contradictory nature of existing guidelines and pedagogical advice to current and future instructors in emergency management.
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