Automation index
How much of a Epidemiologist’s job can AI already do?
A model and a mapped outbreak come earlier. Calling the measure and getting people to follow it do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Epidemiologist
31%
AI can already do 31% of this job.
#34 / 733
View rankingEpidemiologist
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 |
|---|---|---|---|
Surveillance, rates and the outbreak on the map.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Studies, bias and the report for public health.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 48% | +7.7 |
Surveys, contacts and the case interview.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Committee, the unpopular measure and the press.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Field, the care-home outbreak and dirty data.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Judgement, uncertainty and signing the alert.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 31% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- watch outbreaks
- compute rates
- epi studies
- case interviews
- map epidemics
- public-health measures
- contact tracing
- health alerts
Sources for this job· O*NET 19-1041.00· ESCO/ISCO 2263
IS WORK OVER?
Reliability engineer
27%
#175 / 733
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