Automation index
How much of a Astronomer’s job can AI already do?
A night of telescope time comes earlier. Reducing the data without selling the find early do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Astronomer
27%
AI can already do 27% of this job.
#139 / 703
View rankingAstronomer
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.
| Task | Share | AI | Points |
|---|---|---|---|
Proposal, time and the instrument.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Observe, calibrate and the one that clouds over.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Reduce, the pipeline and the artefact.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Paper, the referee and not jumping.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The facility, the queue and not losing the night.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Reduce, and not selling the find early.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- telescope time
- calibrate
- pipelines
- papers
- artefacts
- nights
- proposals
- instruments
Sources for this job· O*NET 19-2011.00· ESCO/ISCO 2111
IS WORK OVER?
Instructional designer
27%
#158 / 703
View rankingInstructional designer
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.
| Task | Share | AI | Points |
|---|---|---|---|
Aim, the storyboard and the module.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Pilot, the learner and what is not understood.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Activity, the feedback and not putting a silly test.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
LMS, the figure and not inflating completion.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The client, the deadline and not cutting the practice.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That they learn, and not leaving the empty video.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- course storyboard
- modules
- learner pilot
- activities
- LMS
- completion
- feedback
- not a silly test
Sources for this job· O*NET 25-9031.00· ESCO/ISCO 2351