LO
Delivery rider / courier — 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
● 2 verified events for this occupation, plotted at the date it happened — the parts of the line near a marker are anchored to something checkable.
The cognitive half of this job was automated before 2022: the platform decides what to deliver and which way to go. So the baseline is 30 and almost everything left is the last fifty metres — a lift with a code, a gate, a sixth floor. Every alternative solves the ride and fails at the door, which is why this is one of the flattest curves here.
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
- 2026-09-10
- Basis of the task judgements
- 2 evidence-backed · 3 platform inference · 0 not enough evidence
- Verified events
- 2