IS WORK OVER?

Automation index

How much of a Judicial police officer’s job can AI already do?

A warrant comes earlier. Lifting the trail without breaking the chain do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Judicial police officer

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
Warrant, the judge and the deadline.
Estimate

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

16%32%+5.1
Scene, the trail and not treading it.
Estimate

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

22%8%+1.8
Entry, the search and the witness.
Estimate

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

16%22%+3.5
Chain, the seal and not breaking it.
Estimate

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

16%28%+4.5
The prosecutor, the rush and not jumping to a yes.
Estimate

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

16%18%+2.9
Lift the trail, and not breaking the chain.
Estimate

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

14%12%+1.7
Total100%19%

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

Skills and activities

  • warrants
  • the scene
  • searches
  • chain of custody
  • seals
  • trails
  • the judge's deadlines
  • witnesses

Sources for this job· O*NET 33-3021.00· ESCO/ISCO 5412

Traffic 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.

TaskShareAIPoints
Counts, the model and the microsim.
Estimate

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

18%48%+8.6
Junction, the timings and the pedestrian.
Estimate

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

16%40%+6.4
Works, the diversion and not choking the neighbourhood.
Estimate

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

16%22%+3.5
Report, the councillor and not painting the miracle lane.
Estimate

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

16%28%+4.5
The crash, the figure and not hiding it.
Estimate

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

18%14%+2.5
That the junction does not kill, and not painting extra.
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

  • microsims
  • counts
  • junction timings
  • pedestrians
  • diversions
  • councillors
  • crashes
  • lanes

Sources for this job· O*NET 17-2051.00· ESCO/ISCO 2142

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