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A/KAI Kills What?

Dossier #213 // technical exposure assessment

High exposure

Robotics Engineers

Category: General · SOC 17-2199.08 · Industry: Cross-industry

AI Exposure (AI-estimated)

n/a
-

Not assessed

Last updated

unknown

sources: BLS OES (approx) · O*NET

Evidence

0 sources

20 core tasks shown

Verdict

Robotics Engineers High exposure: 4 of 20 core tasks show high task automation potential : exposure 50/100 (not assessed).

No model has published evidence mapped to this occupation yet - the score comes from generic task assessment.

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Score breakdown

Why this score?

Every component is stored with the score row and can be recomputed from the evidence table.

AI Exposure (composite)n/a/100

Methodology - · score - · input hash -

AI capability exposuren/a/100

Strength of current models on the capabilities this job's tasks require.

Task automation potentialn/a/100

Task-level exposure, weighted by task importance. A component of the headline, not the headline itself.

Observed AI adoptionn/a/100

Evidence that AI is actually being used for this work.

Labour-market signaln/a/100

Observed changes in postings, employment or earnings.

Evidence strengthn/a/100

Quantity and source quality of the evidence behind the score.

0 evidence item(s) contribute. Calculated -.

Overview

Research, design, develop, or test robotic applications.

Employment

-

approx. BLS OES

Median wage

-

approx. BLS OES

Tasks tracked

20

linked to this occupation

Employment and wage values are approximate reference figures from the BLS Occupational Employment and Wage Statistics programme, stored with an approximation flag. Verify against the O*NET record and BLS before quoting them.

Tasks

Task-level automation exposure

Core tasks only. Exposure describes how much of the task output current AI can produce or substantially assist - not whether the task disappears. Secondary shared-baseline edges are hidden until per-occupation curation is complete.

Evidence

Evidence trail

0 attributed item(s). Confidence reflects study design: randomised and production deployments score higher than platform observations, which score higher than projections.

No occupation-specific evidence has been mapped yet. This occupation is scored from generic task assessment only - a genuinely weaker basis, and the reason its score is marked low-confidence.

Historical trend

Exposure over time

Backcast series: recomputed at quarterly checkpoints using only the models and evidence published by each date.

No series yet

This chart fills in once the first snapshot is recorded.

Reconstruction, not measurement. 0 observed daily snapshot(s) exist for this occupation; the earlier part of the curve is derived by applying the current methodology to the model releases and published evidence available at each past date.

Recent events

Signals affecting this occupation

No events match this filter yet. New verified events appear here as analysis completes.

Related

Related Occupations

Occupations sharing major SOC group (17) with Robotics Engineers.

faq

Frequently Asked Questions

Common questions regarding Robotics Engineers and AI exposure.

Will AI replace Robotics Engineers?

Current AI models show an exposure score of 50/100 for Robotics Engineers. This measures technical capability to assist or automate specific tasks rather than predicted immediate job loss. Moderate exposure reflects assistance in routine information-handling while core responsibilities require human judgment.

Which tasks in Robotics Engineers have the highest AI exposure?

The most exposed tasks for Robotics Engineers include "Process or interpret signals or sensor data." (85% exposure) and "Create back-ups of robot programs or parameters." (85% exposure).

What aspects of Robotics Engineers can AI not do yet?

Tasks with the lowest AI exposure for Robotics Engineers include "Install, calibrate, operate, or maintain robots." (5% exposure) and "Supervise technologists, technicians, or other engineers." (5% exposure). These responsibilities typically require physical dexterity, licensed human accountability, or complex interpersonal navigation.

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Notice: All ratings shown are AI-estimated technical exposure scores measuring technical capabilities across O*NET task statements, not predicted job loss. Contains information from O*NET 31.0 by the U.S. Department of Labor, ETA, used under CC BY 4.0.