IS WORK OVER?

Automation index

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

A workshop and a leaflet come earlier. Reaching the person who never walks into the clinic do not.

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

Task comparison

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

Lighting 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
Calc, Dialux and the standard.
Estimate

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

18%48%+8.6
Works, the point and the one that was not put in.
Estimate

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

16%40%+6.4
Night, the glare and the pedestrian.
Estimate

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

16%22%+3.5
Saving, the LED and not leaving the crossing dark.
Estimate

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

16%28%+4.5
The council, the complaint and not dressing the lux.
Estimate

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

18%14%+2.5
That you can see, and not glaring.
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

  • Dialux
  • lux
  • glare
  • lighting points
  • LED
  • crossings
  • lighting standards
  • calcs

Sources for this job· O*NET 17-2199.00· ESCO/ISCO 2149

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