IS WORK OVER?

Automation index

How much of a Aid worker’s job can AI already do?

A logframe comes earlier. Being there when it goes wrong, and doing no harm, do not.

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

Task comparison

Aid worker

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
Forms, logframe and the indicators.
Estimate

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

16%44%+7
The field, local partners and what the spreadsheet misses.
Estimate

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

18%14%+2.5
Donor reports and the paperwork.
Estimate

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

16%32%+5.1
Security, evacuation and the call to stay.
Estimate

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

16%22%+3.5
Community, conflict and not replacing the local.
Estimate

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

18%18%+3.2
Do no harm and owning the project.
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

  • logframe
  • field work
  • justify projects
  • local partners
  • mission security
  • aid indicators
  • donor reports
  • do no harm

Sources for this job· O*NET 21-1093.00· ESCO/ISCO 2635

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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