IS WORK OVER?

Automation index

How much of a Parking attendant’s job can AI already do?

A barrier comes earlier. Running the car park without wrecking the person who lost the ticket do not.

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

Task comparison

Parking attendant

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
Barriers, tickets and the count.
Estimate

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

16%40%+6.4
The one who cannot find the car and the one who will not pay.
Estimate

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

18%14%+2.5
Incidents, the down barrier and the jam.
Estimate

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

16%28%+4.5
Shift, cash and cashing up.
Estimate

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

16%32%+5.1
The event, the full house and not blocking the street.
Estimate

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

18%18%+3.2
Run the car park, and not wrecking the lost-ticket person.
Estimate

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

16%12%+1.9
Total100%24%

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

Skills and activities

  • barriers
  • parking tickets
  • space count
  • cashing up
  • stuck barrier
  • events
  • lost cars
  • exit jam

Sources for this job· O*NET 33-9091.00· ESCO/ISCO 5414

Statistician

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
Model, clean and visualise.
Estimate

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

20%48%+9.6
Design sample, experiment and biases.
Estimate

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

16%32%+5.1
Client, questions and not overfitting.
Estimate

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

16%22%+3.5
Reproducibility, code and documentation.
Estimate

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

16%18%+2.9
Publication, review and data ethics.
Estimate

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

16%16%+2.6
Not selling a p-value that does not hold.
Estimate

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

16%14%+2.2
Total100%26%

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

Skills and activities

  • Model, clean and visualise
  • Design sample, experiment and biases
  • Client, questions and not overfitting
  • Reproducibility, code and documentation
  • Publication, review and data ethics
  • Not selling a p-value that does not hold
  • estadistico
  • statistician

Sources for this job· O*NET 15-2041.00· ESCO/ISCO 2120

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