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

Station master

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
Graph, orders and the station log.
Estimate

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

16%40%+6.4
Platforms, the crossing and the late train.
Estimate

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

18%14%+2.5
Staff, shifts and the ticket-office gap.
Estimate

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

16%32%+5.1
Incident, passengers and the PA.
Estimate

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

16%22%+3.5
Works, closures and leaving nobody on the platform.
Estimate

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

18%18%+3.2
That they do not meet, and signing the graph.
Estimate

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

16%12%+1.9
Total100%23%

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

Skills and activities

  • train graph
  • orders
  • platforms
  • ticket office
  • PA
  • line crossings
  • station shifts
  • station logs

Sources for this job· O*NET 53-4031.00· ESCO/ISCO 4323

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