IS WORK OVER?

Automation index

How much of a Olive-oil miller’s job can AI already do?

A yield comes earlier. Cold extracting without overheating do not.

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

Task comparison

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

Translator

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
Follow ethical codes that protect the confidentiality of information.
Estimate

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

15%28%+4.2
Translate messages simultaneously or consecutively into specified languages, orally or by using hand signs, maintaining message content, context, and style as much as possible.
Public

WMT 2024

See evidence

14%72%+10.1
Listen to speakers' statements to determine meanings and to prepare translations, using electronic listening systems as necessary.
Public

WMT 2024

See evidence

11%72%+7.9
Identify and resolve conflicts related to the meanings of words, concepts, practices, or behaviors.
Estimate

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

10%28%+2.8
Check translations of technical terms and terminology to ensure that they are accurate and remain consistent throughout translation revisions.
Public

WMT 2024

See evidence

8%72%+5.8
Refer to reference materials, such as dictionaries, lexicons, encyclopedias, and computerized terminology banks, as needed to ensure translation accuracy.
Public

WMT 2024

See evidence

7%72%+5
Compile information on content and context of information to be translated and on intended audience.
Public

WMT 2024

See evidence

7%72%+5
Adapt translations to students' cognitive and grade levels, collaborating with educational team members as necessary.
Public

WMT 2024

See evidence

7%72%+5
Other less frequent tasks (weight estimated from frequency).
Estimate

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

21%28%+5.9
Total100%52%

Modelled workweek: 100% · Public evidence: 54% · Estimate: 46% · Confidence: Medium

Skills and activities

  • translate texts
  • interpret
  • proofread translations
  • information confidentiality
  • spelling
  • office software
  • grammar
  • speak different languages
  • master language rules
  • develop a translation strategy

Sources for this job· O*NET 27-3091.00· ESCO/ISCO 2643

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