IS WORK OVER?

Automation index

How much of a Hearing aid technician’s job can AI already do?

An earmould and a gain curve come earlier. Getting the patient to hear and live with it do not.

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

Task comparison

Hearing aid technician

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
Audiometry, thresholds and the fitting.
Estimate

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

16%40%+6.4
Take the mould, trial and the one who hates the whistle.
Estimate

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

18%18%+3.2
Program, verify and retune the aid.
Estimate

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

16%32%+5.1
Repair, batteries and aftercare.
Estimate

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

16%28%+4.5
Explain, family and the stigma of the device.
Estimate

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

18%14%+2.5
That they actually hear, and not taking the aid back.
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

  • fit hearing aids
  • take earmoulds
  • audiometry
  • program aids
  • verify gain
  • repair aids
  • hearing thresholds
  • aftercare

Sources for this job· O*NET 29-2092.00· ESCO/ISCO 3214

Olive-oil miller

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
Intake, yield and the mill log.
Estimate

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

16%40%+6.4
Crush, malaxate and the decanter.
Estimate

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

18%12%+2.2
Temperature, time and the fruitiness.
Estimate

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

16%28%+4.5
Cellar, the batch and the one that goes rancid.
Estimate

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

16%22%+3.5
The campaign, the tractor queue and not heating.
Estimate

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

18%18%+3.2
Cold for real, and not painting the yield.
Estimate

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

16%12%+1.9
Total100%22%

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

Skills and activities

  • crush olives
  • malaxation
  • decanter
  • fruitiness
  • the campaign
  • mill yield
  • oil cellar
  • extraction temperature

Sources for this job· O*NET 51-3092.00· ESCO/ISCO 7514

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