Aim: This paper reviews the prevalence of generative artificial intelligence (GAI), analyses the ethics of GAI in academic writing, and evaluates ethical implications on academic integrity and quality lastly, we identify and propose solutions to the challenges identified.
Method: A descriptive review which is a fact-finding mission that exposes or determines the interpretable pattern shaping a given research topic was used. The existing documents on the subject matter were searched, screened, classified, and reviewed through a literature review. Study questions were defined; relevant studies were identified and selected. The data about the studies were charted; collated and summarized lastly the results were reported.
Results: The pervasiveness of AI has been identified in the areas of grammar and formatting, plagiarism detection, content generation, and research assistance. In the purview of ethical concerns, plagiarism is more conspicuous and incidentally affects the severity of the other ethical concerns in one way or another. Authorship has been acknowledged to connote responsibility and thus arguments about authorship and co-authorship need consent to secure accountability. The paper also explored transparency and bias in using AI in academic writing. The acquisition of data used in training and how training is done; the black box concepts that hold the transparency element and how to remedy its effects. Further, moral, legal, and fair uses were reviewed, converging at a legal understanding. Equality in the academic journey exposed equity concerns including access and affordance, legal constraints, and bans in some parts of the world.
Conclusion: AI can assist in grammar and formatting, plagiarism detection, content generation and research assistance. However, ethical, legal as well as moral framework guiding application of GAI is necessary to enable proper use that is acceptable and beneficial to the society in general. Disclosure encourages ethical principles. Openness, honesty transparency, etc. can be cultivated when sources used in academic writing are declared. The value of research is realized when it is published and it can be reproducible. This can happen if it is credible and authentic. The synthesis required for foundational literature to anchor the research should be judged by a human author and not a machine to aid originality.
Key words: Generative artificial intelligence, academic writing, and research, ethics, authorship, plagiarism, co-authorship, legal.
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