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 / 623
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?
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