The GPT language model, developed by OpenAI, has gained widespread attention for its impressive ability to engage in conversational interactions with human users, thanks to its extensive training on vast amounts of written data. However, it is crucial to acknowledge that GPTs and their derivatives can exhibit unethical behaviors. Despite this, there has been limited research conducted on the ethical implications of Large Language Models (LLMs) in higher education. To address these concerns, this paper aims to comprehensively examine the harmful behaviors displayed by GPT and its spin-offs. These behaviors encompass social and monolingual biases, issues of reliability and trustworthiness, data privacy and security concerns, toxicity in generated content, challenges in human-computer interaction, and environmental impact.by conducting this study, valuable insights will be provided to educators, administrators, and students, enhancing their awareness of the ethical risks inherent in GPT and its various versions. This will enable them to proactively address and mitigate potential ethical concerns arising from the use of LLMs in educational settings.

The emergence of large language models such as Chat Generative Pretrained Transformer (GPT) has resulted in a paradigm shift in the education space. GPT, released by OpenAI, can generate suitable responses to human input text in a conversational style, making it attractive for laborious written tasks, such as summarizing and responding to questions in higher education institutions. While several studies reveal the real implementations of GPT in higher education institutions, a comprehensive examination of its potential at the micro and macro levels of higher education is lacking. To address this gap, the researchers of this study examined the potential capabilities of GPT through three lenses: student-facing, teacher-facing, and system-facing tools. The purpose of this study is to provide a robust and nuanced understanding of the appropriateness of GPT’s use among stakeholders, such as educators, administrators, and students in higher education. Finally, the study presents a set of applicable recommendations for future researchers.