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?
Mobile developer
28%
#92 / 633
View rankingMobile developer
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 |
|---|---|---|---|
Screens, API and offline state.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Store review, crashlytics and ANRs.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Real device, the notch and fragmented Android.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
CI, tests and the week's release.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Product, the redesign and not breaking what people use.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it does not crash, and not ignoring the one-star.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 28% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- build apps
- ship to stores
- crashlytics
- offline state
- ANRs
- mobile tests
- fragmented Android
- store review
Sources for this job· O*NET 15-1252.00· ESCO/ISCO 2514