IS WORK OVER?

Automation index

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

Urban ATO comes earlier. Crossing pedestrians without clipping the badly parked car do not.

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

Task comparison

Tram driver

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
Checks, log and the cab.
Estimate

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

16%32%+5.1
Drive, stops and the pedestrian who steps out.
Estimate

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

24%8%+1.9
Badly parked car, calls and Control.
Estimate

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

16%22%+3.5
Timetable, reliefs and rush hour.
Estimate

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

16%28%+4.5
The tourist, the bike and not over-hooting.
Estimate

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

14%18%+2.5
Hit nobody, and make the terminus.
Estimate

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

14%12%+1.7
Total100%19%

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

Skills and activities

  • drive trams
  • urban stops
  • pedestrians
  • badly parked cars
  • Control
  • rush hour
  • cab checks
  • terminus

Sources for this job· O*NET 53-4041.00· ESCO/ISCO 8311

Public health officer

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
Surveillance, the indicator and the alert.
Estimate

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

16%40%+6.4
Outbreak, the questionnaire and the one who will not answer.
Estimate

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

18%14%+2.5
Field, the source and shutting the premises.
Estimate

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

16%28%+4.5
Report, the mayor and not softening the figure.
Estimate

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

16%22%+3.5
Vaccination, coverage and the rumour.
Estimate

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

18%18%+3.2
Cut the outbreak, and not softening it.
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

  • epi surveillance
  • outbreaks
  • field questionnaires
  • shut premises
  • vaccine coverage
  • public-health alerts
  • mayors
  • not soften figures

Sources for this job· O*NET 21-1091.00· ESCO/ISCO 2263

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