LO
Dentist — 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 digital X-rays, scanning and practice software were already standard before this chart begins, and rises with the arrival of cleared AI that reads radiographs and drafts records — the cognitive edge of the job. It stays low because the core is hand work on a conscious patient and a diagnosis the law assigns to a registered dentist; the AI tools regulators have cleared are cleared as aids to that dentist, so they add accuracy beneath the decision rather than taking it.
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
- 2026-09-24
- Basis of the task judgements
- 4 evidence-backed · 2 platform inference · 0 not enough evidence
- Verified events
- 2