Environmental journalism is vital for raising awareness of ecological crises and driving evidence-based policy, yet traditional methods falter under delays, inaccuracies, and scalability limits, especially in under-monitored regions critical to the United Nations Sustainable Development Goals. To bridge these gaps, this paper introduces the AI-Environmental Journalism Integration Model (AEJIM), an innovative framework combining real-time hazard detection, automated reporting, crowdsourced validation, expert review, and transparent dissemination.
View on arXiv@article{tiltack2025_2503.17401,
title={ AIJIM: A Scalable Model for Real-Time AI in Environmental Journalism },
author={ Torsten Tiltack },
journal={arXiv preprint arXiv:2503.17401},
year={ 2025 }
}