The ethical complexities of using AI in academic research

THERE has been increasing attention given to the role of Artificial Intelligence (AI) at universities and its role in the knowledge economy. Continual debates about concerns regarding the originality of content and its alignment with reality, and truth are what many academics are concerned about.

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Artificial Intelligence is predominantly based on datasets and algorithms, which can pose a problem when it comes to accuracy, timeliness and contextually relevant details.

This can become problematic, especially if research is based in localities that are not necessarily well-known to people or where there has been limited research development and engagement.

Some platforms of Artificial Intelligence respond with broad brushstrokes as we enter a query, and then there are others that are more academically defined and can resource appropriate literature with citations and appropriate literature.

The challenge now ahead of academics and researchers employed at universities is how to manage to effectively identify and query work presented by students who have used an artificial intelligence platform.

The most commonly utilised platform at present is Turnitin, which quickly picks up a percentage of similarity between work published and the student's work. Its key performance is benchmarked on the identification of plagiarism, but what about the ethics involved when utilising artificial intelligence platforms for academic writing and research? Some international journals have clearly stipulated that Artificial Intelligence platforms are utilised in the write-up process of the research article.