A Scalable AI-Based System for Evaluating and Enhancing Responsible Media Coverage of Suicide: A Multi-Site, Multi-Language Implementation Study
Y. Levi-Belz, Z. ElyosephIntroduction
Irresponsible media coverage of suicide can increase suicide rates through the “Werther effect,” while responsible reporting can reduce risk and stigma. Although the WHO has issued clear guidelines for responsible reporting, adherence remains inconsistent worldwide due to structural barriers and the lack of real-time tools for journalists.
Objectives
This study aimed to develop and rigorously evaluate a multilingual GenAI-based system that can automatically assess and enhance suicide-related news articles to align with WHO guidelines, offering a scalable pathway for more responsible coverage.
Methods
A total of 120 suicide-related articles (English, Hebrew, and French) were systematically selected and independently evaluated for guideline adherence by both expert human raters and the AI system. The articles were automatically revised using the AI correction module. Post-enhancement, all articles were re-evaluated by the system and by a new set of human raters to compare changes in adherence levels.
Results
The AI system demonstrated high agreement with human raters at baseline (ICC = .77), with slight conservative bias in some languages. Following the AI-based enhancement bot, both AI and human evaluations confirmed significant improvements in guideline adherence (mean scores increased from ~45% to ~85%), with no significant post-enhancement differences between human and AI ratings.
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