LO
Radiographer / radiologic technologist — 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 18 because digital imaging, automatic exposure control and the picture archive were standard before this chart begins, and rises as deep-learning reconstruction, positioning aids and image-quality checks arrive inside the scanners, and as triage software starts reading images as they are taken — the machine side of the job. It stays low because the core is a person positioned, protected and watched during an examination, and Singapore's law describes that work, radiation dose included, as a profession practised under the radiographer's title only by a qualified person. None of its steps follow a language-model release.
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
- 2026-09-25
- Basis of the task judgements
- 2 evidence-backed · 4 platform inference · 0 not enough evidence
- Verified events
- 1