AI Hallucinations in Academic Writing and Addresses
TL;DR
The study reveals that AI hallucinations have three kinds of manifestations, which include content distortion, evidence failure and improper argumentation, which comprises factual error, false or irrelevant citation, and superficially coherent arguments lacking evidence.
Abstract
The generative artificial intelligence (AI) has been widely used in academic writing, and its hallucination issue becomes problematic when considering the accuracy and credibility of academic writing. The systematic literature review methodology is used in this paper, in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) process to filter articles related to the topic since 2022, with the aim of examining the influence of AI hallucinations on academic writing. The study reveals that AI hallucinations have three kinds of manifestations, which include content distortion, evidence failure and improper argumentation, which comprises factual error, false or irrelevant citation, and superficially coherent arguments lacking evidence. They may destroy the authenticity, transparency, and logic of academic writing. Even if technologies like Retrieval-Augmented Generation (RAG) and Meta-RAG were able to reduce the hallucination effect at least partially, it would not be possible to completely get rid of it. AI need to be considered as an additional tool, and people are still responsible to verify the information and adhere to academic standards. It is crucial to note that developing critical use skills of AI-generated texts by students in educational environments is very important.