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

Histology technician

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, the pot and not mixing cases.
Estimate

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

16%32%+5.1
Process, embed and the block.
Estimate

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

22%8%+1.8
Cut, the knife and the one that falls apart.
Estimate

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

16%22%+3.5
Stain, the control and the one that will not take.
Estimate

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

16%28%+4.5
The pathologist, the rush and not sending a bad cut.
Estimate

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

16%18%+2.9
Not losing the diagnosis on the knife.
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

  • paraffin blocks
  • histology cutting
  • stains
  • tissue processor
  • not mix cases
  • microtome knife
  • stain controls
  • embedding

Sources for this job· O*NET 29-2012.00· ESCO/ISCO 3212

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