Exposure to disturbing imagery can significantly impact individuals, especially professionals who encounter such content as part of their work. This article presents a user study, involving 107 participants, predominantly journalists and human rights investigators, that explores the capability of Artificial Intelligence (AI)-based image filters to potentially mitigate the emotional impact of viewing such disturbing content. We tested five different filter styles, both traditional (Blurring and Partial Blurring) and AI-based (Drawing, Colored Drawing, and Painting), and measured their effectiveness in terms of conveying image information while reducing emotional distress. Our main findings suggest that the AI-based Drawing style filter demonstrates the best performance, offering a promising solution for reducing negative feelings (−30.38%) while preserving the interpretability of the image (97.19%). Overall, this article contributes to the development of a more ethically considerate and effective visual environment for professionals routinely engaging with potentially disturbing imagery.

This paper gives an overview of the First International Workshop on Multimedia Verification, organized as part of the 2017 ACM Multimedia Conference. The paper outlines the current verification scene and needs, discusses the goals of the workshop, and presents the workshop's program, consisting of two invited keynote talks and three presentations of full papers that have been accepted at the workshop.