IS WORK OVER?

Automation index

How much of a Hydraulic engineer’s job can AI already do?

A floodplain model comes earlier. Sizing the channel so the village does not flood do not.

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

Task comparison

Hydraulic engineer

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
Hydrology, flows and the floodplain model.
Estimate

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

18%48%+8.6
Field, section and what LiDAR misses.
Estimate

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

16%22%+3.5
Drainage works, pumps and the outfall.
Estimate

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

16%36%+5.8
Water permits and the river authority.
Estimate

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

16%28%+4.5
The flood, the village and the yes to the channel.
Estimate

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

18%14%+2.5
That it does not flood, and not trusting the model alone.
Estimate

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

16%12%+1.9
Total100%27%

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

Skills and activities

  • model floodplains
  • flows
  • drainage
  • channel works
  • water permits
  • pumps
  • channel sections
  • river authority

Sources for this job· O*NET 17-2051.00· ESCO/ISCO 2142

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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