Automation index

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

A current model comes earlier. Going to sea and actually reading the water do not.

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

Task comparison

IS WORK OVER?

22%

AI can already do 22% of this job.

#357 / 633

Oceanographer

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
Model, buoys and the cruise. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Sea, sampling and the one who misses the cast. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
Data, the gap and not interpolating extra. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Report, the coast and the one who will not hear. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
The storm, the ship and aborting. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
Read the water, and not trusting the model alone. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Total	100%		22%

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

IS WORK OVER?

25%

#230 / 633

Biomedical engineer

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
Design, validate and document clinical devices and software. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Tests, MDR and risk. Estimate No public source provides a precise figure. This is our estimate.	16%	32%	+5.1
Hospital, clinicians and maintenance. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Vendors, quality and traceability. Estimate No public source provides a precise figure. This is our estimate.	16%	18%	+2.9
User training and post-market watch. Estimate No public source provides a precise figure. This is our estimate.	18%	16%	+2.9
Not putting a half-built prototype in theatre. Estimate No public source provides a precise figure. This is our estimate.	16%	14%	+2.2
Total	100%		25%

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