Automation index
How much of a Ice-cream maker’s job can AI already do?
A base recipe comes earlier. Creamy in the mouth without turning to ice do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Ice-cream maker
22%
AI can already do 22% of this job.
#338 / 633
View rankingIce-cream maker
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 |
|---|---|---|---|
Base, overrun and the recipe.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 44% | +7 |
Churn, age and the one that crystals.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 12% | +2.2 |
List, season and the flavour that misses.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Workshop, cold and the broken chain.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Summer, the queue and not running out of vanilla.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Creamy in the mouth, and not selling ice.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
- churn
- overrun
- age bases
- ice-cream list
- cold chain
- ice crystals
- vanilla
- ice-cream season
Sources for this job· O*NET 51-3099.00· ESCO/ISCO 7512
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