To Deepfake or Not to Deepfake: Higher Education Stakeholders' Perceptions and Intentions towards Synthetic Media
Journal:
arXiv
Published Date:
Feb 25, 2025
Abstract
Advances in deepfake technologies, which use generative artificial
intelligence (GenAI) to mimic a person's likeness or voice, have led to growing
interest in their use in educational contexts. However, little is known about
how key stakeholders perceive and intend to use these tools. This study
investigated higher education stakeholder perceptions and intentions regarding
deepfakes through the lens of the Unified Theory of Acceptance and Use of
Technology 2 (UTAUT2).
Using a mixed-methods approach combining survey data (n=174) with qualitative
interviews, we found that academic stakeholders demonstrated a relatively low
intention to adopt these technologies (M=41.55, SD=34.14) and held complex
views about their implementation. Quantitative analysis revealed adoption
intentions were primarily driven by hedonic motivation, with a gender-specific
interaction in price-value evaluations. Qualitative findings highlighted
potential benefits of enhanced student engagement, improved accessibility, and
reduced workload in content creation, but concerns regarding the exploitation
of academic labour, institutional cost-cutting leading to automation,
degradation of relationships in education, and broader societal impacts.
Based on these findings, we propose a framework for implementing deepfake
technologies in higher education that addresses institutional policies,
professional development, and equitable resource allocation to thoughtfully
integrate AI while maintaining academic integrity and professional autonomy.
