IS WORK OVER?

Automation index

How much of a Language teacher’s job can AI already do?

A drill and a correction come earlier. Getting a shy person talking for an hour does not.

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

Task comparison

Language teacher

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
Prepare lessons, worksheets and corrections.
Estimate

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

16%48%+7.7
Class, conversation and group dynamics.
Estimate

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

22%12%+2.6
Assess speaking, writing and levels.
Estimate

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

16%22%+3.5
Platform, homework and follow-up.
Estimate

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

16%28%+4.5
Families, schools and official exams.
Estimate

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

16%18%+2.9
Not leaving someone mute in a language.
Estimate

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

14%14%+2
Total100%23%

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

Skills and activities

  • teach class
  • mark students
  • lesson plans
  • teach
  • Class, conversation and group dynamics
  • Assess speaking, writing and levels
  • Platform, homework and follow-up
  • Families, schools and official exams
  • Not leaving someone mute in a language
  • profesor de idiomas

Sources for this job· O*NET 25-3011.00· ESCO/ISCO 2353

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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