Automation index
How much of a History teacher’s job can AI already do?
A causes outline comes earlier. Them not cramming dates and knowing why it happened do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
History teacher
22%
AI can already do 22% of this job.
#439 / 743
View rankingHistory teacher
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 |
|---|---|---|---|
Topic, sources and the outline.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Classroom, the debate and the one who drops the cliché.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Exam, the argument and not rewarding the crib.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Trip, the museum and getting them to actually look.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The family, the politics and not indoctrinating.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
That they know why it happened, and not just the date.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
- historical sources
- causes outlines
- classroom debate
- history exams
- museum trips
- not indoctrinate
- cribs
- argument
Sources for this job· O*NET 25-2031.00· ESCO/ISCO 2330
IS WORK OVER?
Reliability engineer
27%
#176 / 743
View rankingReliability engineer
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, MTBF and the Pareto.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Failure, the cause and not patching twice.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Spare, the critical and not hiding it.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
RCM, the plan and the one that is not done.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Production, the rush and not running the tired one.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it does not drop at three, and not hiding the spare.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- MTBF
- Pareto
- root causes
- critical spares
- RCM
- failures
- maintenance plans
- not patch twice
Sources for this job· O*NET 17-2112.00· ESCO/ISCO 2141