AI exposure: Forest Fire Inspectors and Prevention Specialists
Enforce fire regulations, inspect forest for fire hazards, and recommend forest fire prevention or control measures. May report forest fires and weather conditions.
Reading this score
computedAt 18.3% of weighted task load, Forest Fire Inspectors and Prevention Specialists sits at the 31th percentile, below the point where a job's centre of gravity has moved. 58.8% 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 context. Across this occupation's 16 tasks it averages 2.08 out of 3, the highest of the five friction dimensions. In plain terms, the work depends on knowledge the model cannot hold. Much of this job runs on things that were never written down: what this particular organisation does, what happened last week, what the person across the table actually meant. That context is the barrier, and it erodes as systems are given more access.
The most exposed thing this job does is Maintain records and logbooks, at 73.3%. The least is Restrict public access and recreational use of forest lands during critical fire seasons, at 0.0%. A gap of 73.3% 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 protective service occupations, this one is less exposed than the median of 18.9% across the group's 26 roles, with 13 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 16 tasks, 3 are currently banded exposed, 4 assisted and 9 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 | 1.60 | 0-4 |
| Embodiment | 2.07 | 0-3 |
| Presence | 1.89 | 0-3 |
| Accountability | 1.47 | 0-3 |
| Context | 2.08 | 0-3 |
| Verification cost | 1.96 | 0-3 |
Task by task
16 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Maintain records and logbooks. | 73.3% | 26.7% | 0.0% | 3.80 | exposed |
| Educate the public about fire safety and prevention. | 40.0% | 26.7% | 33.3% | 3.96 | exposed |
| Relay messages about emergencies, accidents, locations of crew and personnel, and fire hazard conditions. | 30.0% | 45.0% | 25.0% | 4.57 | assisted |
| Conduct wildland firefighting training. | 26.7% | 23.3% | 50.0% | 4.35 | exposed |
| Locate forest fires on area maps, using azimuth sighters and known landmarks. | 20.0% | 30.0% | 50.0% | 4.30 | assisted |
| Examine and inventory firefighting equipment, such as axes, fire hoses, shovels, pumps, buckets, and fire extinguishers, to determine amount and condition. | 18.8% | 18.8% | 62.5% | 3.98 | untouched |
| Compile and report meteorological data, such as temperature, relative humidity, wind direction and velocity, and types of cloud formations. | 15.0% | 10.0% | 75.0% | 4.09 | untouched |
| Inspect forest tracts and logging areas for fire hazards such as accumulated wastes or mishandling of combustibles, and recommend appropriate fire prevention measures. | 15.0% | 35.0% | 50.0% | 3.21 | assisted |
| Estimate sizes and characteristics of fires, and report findings to base camps by radio or telephone. | 13.3% | 36.7% | 50.0% | 4.35 | assisted |
| Direct maintenance and repair of firefighting equipment, or requisition new equipment. | 12.5% | 25.0% | 62.5% | 3.90 | untouched |
| Inspect camp sites to ensure that campers are in compliance with forest use regulations. | 6.7% | 18.3% | 75.0% | 3.41 | untouched |
| Patrol assigned areas, looking for forest fires, hazardous conditions, and weather phenomena. | 5.8% | 19.2% | 75.0% | 4.10 | untouched |
| Direct crews working on firelines during forest fires. | 1.7% | 23.3% | 75.0% | 4.30 | untouched |
| Administer regulations regarding sanitation, fire prevention, violation corrections, and related forest regulations. | 1.7% | 23.3% | 75.0% | 3.58 | untouched |
| Extinguish smaller fires with portable extinguishers, shovels, and axes. | 0.0% | 0.0% | 100.0% | 4.20 | untouched |
| Restrict public access and recreational use of forest lands during critical fire seasons. | 0.0% | 0.0% | 100.0% | 3.56 | 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.