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
IS WORK OVER?
Tram driver
19%
AI can already do 19% of this job.
#487 / 633
View rankingTram 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.
| Task | Share | AI | Points |
|---|---|---|---|
Checks, log and the cab.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Drive, stops and the pedestrian who steps out.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 8% | +1.9 |
Badly parked car, calls and Control.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Timetable, reliefs and rush hour.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The tourist, the bike and not over-hooting.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 18% | +2.5 |
Hit nobody, and make the terminus.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 12% | +1.7 |
| Total | 100% | 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
IS WORK OVER?
Cartographer
31%
#31 / 633
View rankingCartographer
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.
| Task | Share | AI | Points |
|---|---|---|---|
Sources, OSM, satellite and generalisation.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Symbology, type and visual hierarchy.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 48% | +7.7 |
Projections, scales and getting the heights right.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Review with the client, the field and the lie in the data.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Print maps, web maps and updates.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Credit, metadata and owning the map.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 31% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- make maps
- generalise cartography
- symbology
- choose projection
- visual hierarchy
- update OSM
- web maps
- maps that do not lie
Sources for this job· O*NET 17-1021.00· ESCO/ISCO 2165