LO
Physiotherapist / rehabilitation therapist — 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.
One of the flattest curves on the site, and the small rise it has belongs entirely to programme design — choosing exercises, loads and progressions from a diagnosis and a set of constraints is what software does well, and app-delivered exercise is widely deployed. It stops there because assessment and hands-on treatment are closed-loop physical work in which the control signal is tissue resistance felt through the hands, and because adherence, which decides outcome, is a relationship rather than an instruction. The important caution is that this curve measures the wrong threat: the pressure on this occupation comes from the fee schedule, and it pushes in the same direction software does — toward the parts deliverable without the therapist.
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
- 2026-09-14
- Basis of the task judgements
- 3 evidence-backed · 1 platform inference · 0 not enough evidence
- Verified events
- 2