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.

翻译：能够生成可信却具有合成性质的媒体软件，对全球高等教育既带来威胁也带来益处。尽管存在其他形式的合成媒体，本研究聚焦于深度伪造——即基于真实人物的先进生成式人工智能（GenAI）伪造内容。本文是一篇概念性论文，通过对182篇同行评审出版物进行初步范围综述，评估当前跨学科领域的深度伪造研究文献。综述揭示了三大主要趋势：检测方法、恶意应用及潜在益处，但未发现专门针对高等教育情境下深度伪造的研究。在讨论这些趋势后，本研究将相关发现应用于界定深度伪造技术在高等教育中的主要风险及潜在缓解策略，同时分析其辅助深度伪造与合成媒体教学的双重可能用途。最终，本文提出一项研究议程，旨在构建全面、跨文化的研究路径，以系统探究高等教育中的深度伪造问题。