  The availability of software which can produce convincing yet synthetic media
poses both threats and benefits to tertiary education globally. While other
forms of synthetic media exist, this study focuses on deepfakes, which are
advanced Generative AI (GenAI) fakes of real people. This conceptual paper
assesses the current literature on deepfakes across multiple disciplines by
conducting an initial scoping review of 182 peer-reviewed publications.
  The review reveals three major trends: detection methods, malicious
applications, and potential benefits, although no specific studies on deepfakes
in the tertiary educational context were found. Following a discussion of these
trends, this study applies the findings to postulate the major risks and
potential mitigation strategies of deepfake technologies in higher education,
as well as potential beneficial uses to aid the teaching and learning of both
deepfakes and synthetic media. This culminates in the proposal of a research
agenda to build a comprehensive, cross-cultural approach to investigate
deepfakes in higher education.
