Research journeys · Record 001
How my research into AI and environmental journalism began
A photograph shows a possible environmental problem. How does it become a reliable story? My first published research paper explored how AI and human review could work together along the way.
- Talk
- FTC 2025 · 7:24 min · English
- Paper published
- 16 October 2025
- Context
- Early AIJIM research
The original talk · FTC 2025
AI in Environmental Journalism
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The question behind it
A picture is a starting point. The reporting is still to come.
A photo shows dumped waste. But where is it? What can the image actually tell us? And who checks the interpretation before it becomes a report? You don’t need an AI background to follow those questions.
The paper connects automated image analysis, human participation and report generation. NamicGreen provided the application context for the described 2024 Mallorca pilot. The interaction between these steps is central to the approach.
Paper & sourcesFrom photograph to report
The earlier approach in six steps, simplified from the freely available preprint. Human review is an explicit part of the described process.
- 01
Observe
A photograph with location information is submitted.
- 02
Analyse
AI looks for clues in the image.
- 03
Draft
An initial report is generated.
- 04
Check
People check the detections.
- 05
Review
Experts and community members review the report.
- 06
Publish
The reviewed report is shared.
What the paper reports
A pilot in Mallorca.
The published abstract describes a pilot involving 1,000 images and 50 previously undocumented waste sites. The figures below reproduce the outcomes reported in the paper. They have not been newly measured or independently recalculated for this record.
Explore the pilot’s reported figures
- reported detection accuracy
- 85.4%
- reported agreement with expert annotations
- 89.7%
- reported reduction in reporting latency
- 40%
These figures describe different measures within the original study setting. They are not a general AI reliability rate or a performance promise for current systems.
Where to go from here
One step on my research journey.
The early work grew out of environmental journalism. My current PhD at UTS explores the traceability of AI-assisted claims. You can find the current research and connected projects here, each with its own status.
- My research today
UTS, AIJIM and the questions behind my work.
- NamicGreen today
Follow the independent environmental project.
- AIJIM SHARK
Explore my current experimental editor environment.
Read the originals
The sources behind this record.
The published chapter, earlier preprint and talk are different versions and formats of the same work. The preprint is freely available; access to the Springer full text may require a subscription or purchase.
- 01
Published conference chapter
AIJIM: A Scalable Model for Real-Time AI in Environmental Journalism
Torsten Tiltack · FTC 2025, Volume 2 · LNNS 1676 · pp. 398–416
Online since 16 October 2025 · DOI 10.1007/978-3-032-07989-3_26
Publication at Springer - 02
Preprint · freely available
AIJIM: A Scalable Model for Real-Time AI in Environmental Journalism
arXiv:2503.17401v5 · Version dated 28 April 2025
An earlier manuscript version. It should not be treated as identical to the later published chapter or as a second independent study.
Read the preprint on arXiv - 03
Conference talk · English
AIJIM: AI in Environmental Journalism | FTC 2025 Research Talk
Torsten Tiltack · FTC 2025 · existing recording
The talk reflects the research at the time. This companion page places it in context today.
Original talk on YouTube
Take another look
Research moves on. So does this record.
Later additions, corrections and my personal reflection will have a visible place here. These questions remain open for a future revisit:
- What would I investigate differently today?
- Which assumptions have changed?
- What new observation would change my interpretation?
Talk, published chapter and preprint brought together. Historical findings distinguished from the current project context. No new field study or subsequent revisit results yet.
Stay curious.
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