Automation index
How much of a Criminologist’s job can AI already do?
A crime map comes earlier. Understanding why it happens there, and what to do with the repeat offender, do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Criminologist
29%
AI can already do 29% of this job.
#57 / 623
View rankingCriminologist
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 |
|---|---|---|---|
Data, maps and the victimisation report.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Profiles, reoffending and programme evaluation.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Field, interviews and what the spreadsheet misses.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Police, judges and the measure under debate.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Prevention, the neighbourhood and the programme that does not fit.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The opinion, and not selling magic recipes.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 28% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- crime maps
- study reoffending
- victimisation
- evaluate programmes
- situational prevention
- criminological profiles
- reports for judges
- fieldwork
Sources for this job· O*NET 19-3041.00· ESCO/ISCO 2632
IS WORK OVER?
Mobile developer
28%
#92 / 623
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