Privacy Challenges with Human Imposed and AI-Based Filters During Virtual Meetings

Innovative technology has transformed the future of work, making remote communication the norm, users therefore rely on available features in video conference applications to safeguard their privacy. This study explores challenges caused by artificial intelligence (AI) filters specific to noise reduction and virtual backgrounds and human-imposed filters with the mute button feature during video conference calls through the lenses of the privacy paradox theory. Data triangulation shows that privacy filters’ perceived efficacy frequently outweighs their real capabilities. Although users have faith in the tools, particularly those that are human imposed, there are still behavioral and technical challenges. The privacy paradox, in which users’ confidence in their privacy choices coexists with constant risks is best shown by the gap in practice. The contradiction is particularly noticeable in AI-based filters, which offer smooth, intelligent defense but frequently fails in dynamic, individual environments. According to the study's findings, while users are protecting their boundaries, these filters create additional challenges. Platform developers, users, and organizations are suggested to adopt best practices and more user-centric design.