LO
Plumber — 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 9 because drain cameras, leak detectors and job-management software already existed before this chart begins, and climbs slowly as booking platforms, payment apps and language tools take over more of the quoting and paperwork, and as smart meters start reporting leaks on their own — the business around the job. It stays among the lowest on this site because the job itself is hand work in cramped, varied spaces that current robots do not do, and Singapore's law says only a licensed plumber, or someone under a licensed plumber's direct supervision, may carry out the regulated works.
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.
Written about this#
These pieces argue from the same records this page holds, and each of their sections names what it rests on.
Method and sources#
- Assessment date
- 2026-09-25
- Basis of the task judgements
- 2 evidence-backed · 4 platform inference · 0 not enough evidence
- Verified events
- 1