IS WORK OVER?

Automation index

How much of a Radiation oncologist’s job can AI already do?

Assisted contouring comes earlier. Setting the field and not burning healthy tissue do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Radiation oncologist

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Contouring, fractions and the dose plan.
Estimate

No public source provides a precise figure. This is our estimate.

16%48%+7.7
Clinic, the tumour and what can be irradiated.
Estimate

No public source provides a precise figure. This is our estimate.

18%18%+3.2
Simulation, immobilisation and the machine day.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Side effects, pauses and the patient who cannot take it.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
Board, the surgeon and the medical oncologist.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
Signing the plan and the dose that does not erase.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%23%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • contouring
  • plan radiotherapy
  • dosimetry
  • RT simulation
  • fractions
  • tumour board
  • radiation effects
  • immobilise the patient

Sources for this job· O*NET 29-1224.00· ESCO/ISCO 2212

Mobile developer

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Screens, API and offline state.
Estimate

No public source provides a precise figure. This is our estimate.

18%52%+9.4
Store review, crashlytics and ANRs.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
Real device, the notch and fragmented Android.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
CI, tests and the week's release.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
Product, the redesign and not breaking what people use.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
That it does not crash, and not ignoring the one-star.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%28%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • build apps
  • ship to stores
  • crashlytics
  • offline state
  • ANRs
  • mobile tests
  • fragmented Android
  • store review

Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2514

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