Advancing the Potential of VR in Policing:Exploring the Role of Deepfake Technologies in Research and Training - A discussion in the context of over and under policing minorities.
Year: 2025
Type: book-chapter
Abstract: This study explores the potential of virtual reality (VR) in police training. It delves into the use of deepfake technology in an experiment investigating how racist stereotypes influence Dutch police officers’ behaviour in stop-and-search scenarios. In a 2x2 experimental design, 87 officers encountered racist stereotypes and deepfake manipulations in the VR environment. Findings indicate widespread acceptance of VR in policing, consistent with prior research (De Vries et al., 2023), and contrary to previous perceptions, highlighting the near-perfect imperceptibility of deepfake, enhancing VR immersion. Notably, participants exposed to deepfake of a non-white person tended to avoid selecting said ethnic minorities for stop-and-search, hinting at a potential avoidance behaviour. Furthermore, we examined the impact of VR and deepfake on user experience measured through self-reported feelings of presence, engagement, enjoyment and embodiment of police officers in daily work. We used technological mediation theory to explore how these factors influence participants’ perceptions and actions. The study reveals a unique mediation, intertwining individuals, technology, reality and simulation, with participants reporting dual experiences oscillating between immersion and grounding. Reflecting on this interplay, our study underscores the transformative potential of VR and deepfake in policing research and training but highlights the importance of preserving the fidelity of the virtual-to-real-world connection to harness these technologies’ potential effectively.
Authors: Paululat, Meret, Böing, Bas Stefan, Niculescu-Dinca, Vlad, de Vries, Peter W.; id_orcid 0000-0001-9710-8752
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7115230677
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