LO
Cabin crew — 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 14 because onboard sales, stock counts and reports were already moving onto card terminals and tablets before this chart begins, and climbs slowly because what the releases on the axis can reach is only that administrative edge and the ordering channel. It stays low for a reason written into the rules rather than into any technology: the minimum crew is counted by seats and exits for evacuation, so service automation can thin the crew an airline carries above that floor but cannot move the floor itself.
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