ChatGPT and other Generative Artificial Intelligence (GAI) models tend to inherit and even amplify prevailing societal biases as they are trained on large amounts of existing data. Given the increasing usage of ChatGPT and other GAI by students, faculty members, and staff in higher education institutions (HEIs), there is an urgent need to examine the ethical issues involved such as its potential biases. In this scoping review, we clarify the ways in which biases related to GAI in higher education settings have been discussed in recent academic publications and identify what type of potential biases are commonly reported in this body of literature. We searched for academic articles written in English, Chinese, and Japanese across four main databases concerned with GAI usage in higher education and bias. Our findings show that while there is an awareness of potential biases around large language models (LLMs) and GAI, the majority of articles touch on ``bias'' at a relatively superficial level. Few identify what types of bias may occur under what circumstances. Neither do they discuss the possible implications for the higher education, staff, faculty members, or students. There is a notable lack of empirical work at this point, and we call for higher education researchers and AI experts to conduct more research in this area.

翻译：ChatGPT及其他生成式人工智能（GAI）模型在基于大量现有数据进行训练时，倾向于继承甚至放大普遍存在的社会偏见。鉴于高等教育机构（HEIs）中的学生、教师和教职员工对ChatGPT及其他GAI的使用日益增加，亟需审视其潜在的偏见等伦理问题。在本项范围综述中，我们明确了近期学术出版物如何讨论高等教育场景中与GAI相关的偏见，并识别了现有文献中常见报道的潜在偏见类型。我们检索了四个主要数据库中涉及高等教育GAI使用与偏见的英文、中文及日文学术文章。研究发现表明，尽管学术界已意识到大语言模型（LLMs）和GAI潜在偏见的存在，但多数文章对“偏见”的探讨仍停留在相对浅层的水平。鲜有研究具体阐明了何种偏见会在何种情形下产生，亦未讨论其对高等教育机构、教职员工、教师或学生的潜在影响。目前该领域明显缺乏实证研究，我们呼吁高等教育研究者及人工智能专家加强该领域的研究。