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

Front-end 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.

TaskShareAIPoints
Component, states and the design.
Estimate

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

18%48%+8.6
Accessible, the keyboard and the reader.
Estimate

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

16%40%+6.4
Contrast, the token and not leaving it dead.
Estimate

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

16%22%+3.5
Performance, the weight and not adding the extra library.
Estimate

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

16%28%+4.5
The designer, the pixel and not fighting for sport.
Estimate

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

18%14%+2.5
That it works from the keyboard, and not leaving the contrast.
Estimate

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

16%12%+1.9
Total100%27%

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

Skills and activities

  • components
  • accessibility
  • keyboard
  • contrast
  • tokens
  • front-end performance
  • libraries
  • write interface

Sources for this job· O*NET 15-1254.00· ESCO/ISCO 2513

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