IS WORK OVER?

Automation index

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

A corpus comes earlier. Describing the language without over-prescribing do not.

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

Task comparison

Linguist

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
Corpus, glosses and the analysis.
Estimate

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

18%48%+8.6
Field, the speaker and the one who will not.
Estimate

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

16%40%+6.4
Report, the variety and not dismissing it.
Estimate

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

16%22%+3.5
Teach, the standard and not humiliating.
Estimate

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

16%28%+4.5
The job, the rush and not faking the figure.
Estimate

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

18%14%+2.5
Describe, and not over-prescribing.
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

  • corpus
  • glosses
  • varieties
  • speakers
  • the standard
  • linguistic fieldwork
  • analysis
  • not over-prescribe

Sources for this job· O*NET 19-3099.00· ESCO/ISCO 2643

Community health 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
Health map, workshops and the calendar.
Estimate

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

16%40%+6.4
Street, doorway and the neighbour who does not come.
Estimate

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

18%14%+2.5
Vaccines, screening and referring to the clinic.
Estimate

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

16%32%+5.1
Data, report and the health table.
Estimate

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

16%28%+4.5
The rumour, the distrust and not moralising.
Estimate

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

18%18%+3.2
That they come, and not inflating workshop numbers.
Estimate

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

16%14%+2.2
Total100%24%

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

Skills and activities

  • health workshops
  • health map
  • door-to-door
  • refer to clinic
  • screening
  • health table
  • community vaccination
  • health distrust

Sources for this job· O*NET 21-1094.00· ESCO/ISCO 3253

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