Mitigating Viewer Impact From Disturbing Imagery Using AI Filters: A User-Study

Abstract

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.

Keywords:

• Disturbing content
• image style transfer
• journalists
• human rights investigators
• mental health
• artificial intelligence
• gruesome imagery

Ethics statement

All participants were informed why the research is being conducted, whether or not anonymity is assured, and how the data we are collecting is being stored. We confirm that all the subjects have provided appropriate informed consent via the Google Forms platform. Finally, the ethics committee of the Centre for Research and Technology Hellas has granted ethical approval for this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 http://eyewitnessmediahub.com/.

2 https://www.instagram.com/.

Additional information

Funding

This work was supported by the EU H2020 project MediaVerse under Grant Agreement 957252.

Notes on contributors

Ioannis Sarridis

Ioannis Sarridis received both his bachelor’s and master’s degrees from the Department of Informatics at AUTH, Greece, in 2018 and 2020, respectively. He is currently pursuing PhD degree at HUA and is a Research Associate with the CERTH, Greece. His research interests include AI fairness and computer vision.

Jochen Spangenberg

Jochen Spangenberg is Deputy Head of Research and Cooperation Projects at Deutsche Welle. The topical focus of his work over the past decade has been on research dealing with social newsgathering, disinformation analysis and verification of digital content, and relating all this to the news and information sector.

Olga Papadopoulou

Olga Papadopoulou is a research assistant at the Information Technologies Institute, Centre for Research and Technology Hellas and has participated in several EU-funded research projects. Her research interests include natural language processing, multimedia analysis, social network analysis and artificial intelligence.

Symeon Papadopoulos

Symeon Papadopoulos is a Principal Researcher at the Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece. He holds a PhD degree in Computer Science from the Aristotle University of Thessaloniki (2012) on the topic of Knowledge discovery from large-scale mining of social media content.