IS WORK OVER?

Automation index

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

A fibroscan comes earlier. Biopsying the liver and calling the transplant do not.

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

Task comparison

Hepatologist

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
Labs, fibroscan and the stage.
Estimate

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

18%48%+8.6
Clinic, the drink and the one who denies it.
Estimate

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

16%40%+6.4
Biopsy, the risk and not needling extra.
Estimate

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

16%22%+3.5
Antiviral, adherence and the one who quits.
Estimate

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

16%28%+4.5
The transplant board and not jumping to a yes.
Estimate

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

18%14%+2.5
Call the liver, and talking to the family.
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

  • fibroscan
  • liver biopsy
  • hepatitis
  • cirrhosis
  • liver transplant
  • antivirals
  • liver clinic
  • decompensation

Sources for this job· O*NET 29-1216.00· ESCO/ISCO 2212

Social security 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
File, contributions and the right.
Estimate

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

18%48%+8.6
Incapacity, the opinion and the one who cannot.
Estimate

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

16%40%+6.4
Benefit, the deadline and not leaving them unpaid.
Estimate

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

16%22%+3.5
Fraud, the visit and not hunting the poor.
Estimate

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

16%28%+4.5
The doctor, the discharge and not fighting for sport.
Estimate

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

18%14%+2.5
That the right one is paid, and not the one who should not.
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

  • pensions
  • contributions
  • incapacity
  • benefits
  • opinions
  • fraud
  • social-security deadlines
  • medical discharges

Sources for this job· O*NET 13-1141.00· ESCO/ISCO 3353

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