AI exposure: Dredge Operators
Operate dredge to remove sand, gravel, or other materials in order to excavate and maintain navigable channels in waterways.
Reading this score
computedAt 10.2% of weighted task load, Dredge Operators sits at the 14th percentile, below the point where a job's centre of gravity has moved. 84.3% of what this role does is untouched, meaning current systems cannot produce that work at all, whatever the commercial incentive.
What holds the line here is embodiment. Across this occupation's 6 tasks it averages 2.58 out of 3, the highest of the five friction dimensions. In plain terms, the work has to happen in physical space. A language model cannot move matter. Until the robotics to do this work is both good enough and cheap enough to deploy widely, capability in software does not reach it.
The most exposed thing this job does is Pump water to clear machinery pipelines, at 33.3%. The least is Lower anchor poles to verify depths of excavations, at 0.0%. A gap of 33.3% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.
Within transportation and material moving occupations, this one is less exposed than the median of 24.3% across the group's 52 roles, with 44 scoring higher. Being in an exposed family does not make a particular job exposed, and the reverse holds too.
What would move this score. Of 6 tasks, 2 are currently banded exposed, 0 assisted and 4 untouched. For that distribution to shift materially would take robotics cheap and reliable enough to deploy at scale, not a better language model. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.
Where the score comes from
judgedEvery task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.
| Dimension | Mean | Scale |
|---|---|---|
| Capability | 0.67 | 0-4 |
| Embodiment | 2.58 | 0-3 |
| Presence | 0.83 | 0-3 |
| Accountability | 0.92 | 0-3 |
| Context | 1.08 | 0-3 |
| Verification cost | 1.08 | 0-3 |
Task by task
6 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Pump water to clear machinery pipelines. | 33.3% | 16.7% | 50.0% | 4.30 | exposed |
| Direct or assist workers placing shore anchors and cables, laying additional pipes from dredges to shore, and pumping water from pontoons. | 31.7% | 18.3% | 50.0% | 3.83 | exposed |
| Move levers to position dredges for excavation, to engage hydraulic pumps, to raise and lower suction booms, and to control rotation of cutterheads. | 0.0% | 0.0% | 100.0% | 4.82 | untouched |
| Start and stop engines to operate equipment. | 0.0% | 0.0% | 100.0% | 4.41 | untouched |
| Start power winches that draw in or let out cables to change positions of dredges, or pull in and let out cables manually. | 0.0% | 0.0% | 100.0% | 4.31 | untouched |
| Lower anchor poles to verify depths of excavations, using winches, or scan depth gauges to determine depths of excavations. | 0.0% | 0.0% | 100.0% | 3.99 | untouched |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.
Occupations either side of this one
The four closest scores in the same occupational family, then the four closest anywhere in the index.
Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.
What this means in practice
Most of this work is not reachable by current systems, so the immediate pressure is on the administrative edges of the role rather than its core: the scheduling, the reporting, the written records. That is where time is recovered.