IN-PERSON Prague Research & Teaching Conference

Abstract

In the interconnected landscape of contemporary academia, where research, teaching, and practice intersect, the advent of deepfakes and synthetic media presents unprecedented psychosocial risks. This paper explores the ethical, wellbeing, and responsibility dimensions of these technologies within educational and professional settings, using queer and feminist theories as critical lenses. Deepfakes and synthetic media challenge traditional notions of authenticity and truth, raising significant ethical questions about consent, representation, and power dynamics. Queer theory’s interrogation of normativity and feminist critiques of systemic inequities offer valuable frameworks for understanding these challenges. By drawing on three sociotechnical imaginaries, the interdisciplinary approach taken in this paper illuminates how these technologies can perpetuate biases and vulnerabilities, particularly affecting marginalized communities. In the classroom and the field, educators and practitioners must navigate these complexities while fostering an environment of trust and integrity. As such, this paper examines teaching methods that address the ethical implications of synthetic media, promoting critical digital literacy without calling for increased resilience among staff and students. The burden of responsibility cannot be placed on the user; thus, we call for policy changes to mitigate the psychosocial risk of harm from the increasing prevalence and ease of creating deepfakes. We focus on the role of academic institutions in safeguarding mental health and wellbeing, emphasizing the need for novel policies and practices. We conclude by calling for greater importance to be placed on interdisciplinary collaboration and community engagement in developing ethical guidelines and educational frameworks. This approach aims to disrupt the broader discourse around the impact of technology on academia, advocating for a responsible and inclusive approach to teaching and learning.