LO
Firefighter — how we know
The page itself gives the judgements. This one gives what they rest on: which technologies bear on the work, how the estimate moved since language models reached the public, and the method behind both.
Which technologies matter here#
Four separate signals. They are deliberately not added together — a job exposed to two technologies is not twice as exposed.
How it got here#
The index is not a static number. This is where it would have sat at each capability checkpoint since ChatGPT — reconstructed, and labelled as such.
—— this stretch contains a verified event- - - no event in this stretch — reconstruction only0 = no task exposed, 100 = every task exposed
Starts at 16 because remotely operated firefighting machines were already in service before this chart begins, and climbs slowly and almost independently of the model releases on the axis: what moves it is fire services buying ground robots and putting them on engines, a procurement cycle measured in years. The small steps are robots becoming standard kit rather than special equipment. It stays low because the tasks at the centre of the job — searching a building, getting people out, commanding the scene — are not what the robots in service are built to do.
A flat line is not a forecast of safety. It says which tasks automation has reached so far — the occupations that moved least here are the ones where the constraint is physical or regulatory, and both of those can change.
Method and sources#
- Assessment date
- 2026-09-23
- Basis of the task judgements
- 2 evidence-backed · 4 platform inference · 0 not enough evidence
- Verified events
- 2