With the increasing integration of Artificial Intelligence (AI) in our lives, including education, it is necessary to consider and address the ethical questions raised by this process. While the ethics of AI is widely researched, little attention has been paid to the ethics of AI in education (AIED). This systematic literature review aims to identify the main ethical values (EVs) and ethical norms (ENs) for AIED in literature published before 2010 and available in English. Using database search and backward snowballing in November 2022, 25 articles were included and analysed. In order to identify the EVs, the definitions found in literature were collected and reported. Thematic analysis and grouping were performed based on common terms. It was found that there are six main EVs for AIED: non-discrimination, data stewardship, human oversight, goodwill, explicability, and educational aptness. The ENs found in the literature were grouped as per the stakeholder sets that they were relevant for and per main EV. Following this, these two groupings were combined into a matrix with ENs for stakeholder sets to follow in order to implement specific main EVs. Identifying the main components of ethics of AIED is an initial step that can pave the way for future research aimed at creating ethical frameworks or regulation to ethically guide the domain.
Agarwal et al. (Sun,) studied this question.