IS WORK OVER?

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

Epidemiologist

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.

TaskShareAIPoints
Surveillance, rates and the outbreak on the map.
Estimate

No public source provides a precise figure. This is our estimate.

18%52%+9.4
Studies, bias and the report for public health.
Estimate

No public source provides a precise figure. This is our estimate.

16%48%+7.7
Surveys, contacts and the case interview.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
Committee, the unpopular measure and the press.
Estimate

No public source provides a precise figure. This is our estimate.

18%18%+3.2
Field, the care-home outbreak and dirty data.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Judgement, uncertainty and signing the alert.
Estimate

No public source provides a precise figure. This is our estimate.

16%14%+2.2
Total100%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

Logistics analyst

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.

TaskShareAIPoints
Costs, OTIF and the dashboard.
Estimate

No public source provides a precise figure. This is our estimate.

18%52%+9.4
Simulate network, warehouses and the what-if.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
Ops, dirty data and going down to the dock.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Report, the board and the cut that hurts.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The haulier, the contract and not breaking the service.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
A real saving, and not dressing OTIF.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%28%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • logistics costs
  • OTIF
  • simulate network
  • what-if
  • dirty data
  • haulage contracts
  • dashboards
  • network cuts

Sources for this job· O*NET 13-1081.00· ESCO/ISCO 2421

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