Beyond prohibition and permission: A framework for the ethical use of artificial intelligence
TL;DR
It is concluded that originality, authorship, integrity, fairness, and transparency are interdependent concerns rather than separate issues, and that responsible AI use is best understood as a disciplined, disclosed collaboration with a non-author tool.
Abstract
Artificial intelligence (AI) has rapidly transitioned from a research curiosity to a fundamental component of the infrastructure of teaching, research, writing, supervision, and publishing. This conceptual paper contends that the current academic discourse, framed as a binary between prohibition and permission, inadequately addresses the ethical challenges at hand. Drawing upon global AI ethical guidelines, scholarship on academic integrity, and publisher policies, the paper proposes that the ethical utilisation of AI in academic writing should be governed by a coherent system of accountability rather than by isolated regulations. It introduces an original framework, the TRACE model, Transparency, Responsibility, Authorship-accountability, Comprehension, and Equity, as an integrative conceptual tool for educators, researchers, supervisors, editors, and policymakers. This article concludes that originality, authorship, integrity, fairness, and transparency are interdependent concerns rather than separate issues, and that responsible AI use is best understood as a disciplined, disclosed collaboration with a non-author tool.