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

Olive-oil miller

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
Intake, yield and the mill log.
Estimate

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

16%40%+6.4
Crush, malaxate and the decanter.
Estimate

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

18%12%+2.2
Temperature, time and the fruitiness.
Estimate

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

16%28%+4.5
Cellar, the batch and the one that goes rancid.
Estimate

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

16%22%+3.5
The campaign, the tractor queue and not heating.
Estimate

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

18%18%+3.2
Cold for real, and not painting the yield.
Estimate

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

16%12%+1.9
Total100%22%

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

Skills and activities

  • crush olives
  • malaxation
  • decanter
  • fruitiness
  • the campaign
  • mill yield
  • oil cellar
  • extraction temperature

Sources for this job· O*NET 51-3092.00· ESCO/ISCO 7514

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