Automation index
How much of a Ticket inspector’s job can AI already do?
A validator comes earlier. Walking the train and dealing with no ticket do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Ticket inspector
22%
AI can already do 22% of this job.
#378 / 633
View rankingTicket inspector
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 |
|---|---|---|---|
Validate, fares and the intervention note.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Aisle, the group and the one who hides.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 12% | +2.2 |
Fines, data and what you can ask.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Incident, the full train and calling the conductor.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The insult, keeping calm and not making a scene.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Charge fairly, and not skipping a coach.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 22% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- validate tickets
- rail fares
- interventions
- on-train fines
- walk coaches
- call the conductor
- passenger data
- full trains
Sources for this job· O*NET 53-4031.00· ESCO/ISCO 5112
IS WORK OVER?
Statistician
26%
#201 / 633
View rankingStatistician
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 |
|---|---|---|---|
Model, clean and visualise.EstimateNo public source provides a precise figure. This is our estimate. | 20% | 48% | +9.6 |
Design sample, experiment and biases.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Client, questions and not overfitting.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Reproducibility, code and documentation.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Publication, review and data ethics.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 16% | +2.6 |
Not selling a p-value that does not hold.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 26% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Model, clean and visualise
- Design sample, experiment and biases
- Client, questions and not overfitting
- Reproducibility, code and documentation
- Publication, review and data ethics
- Not selling a p-value that does not hold
- estadistico
- statistician
Sources for this job· O*NET 15-2041.00· ESCO/ISCO 2120