29-2053.00

Psychiatric technicians and aides

182,900 workers$42,200/yr medianSee How to Become One
3.2

Lower displacement risk

Composite of 5 dimensions (higher = more displacement pressure)

AI Exposure Analysis

GPT-scored exposure3/10

The core of this occupation involves physical tasks such as bathing, feeding, and physically restraining patients, which AI cannot perform. While AI can assist with monitoring patient behavior and automating documentation or reporting, the high requirement for real-time human presence, physical stamina, and interpersonal compassion creates a significant barrier to automation.

Dimension Breakdown

Technical AI Exposurepressure
3.0

How many of this occupation's tasks can current or near-term AI systems perform? Based on GPT-scored analysis of 342 BLS occupations validated against 6 academic exposure indices.

Institutional Adoption Speedpressure
1.2

How quickly will firms in this sector actually deploy AI? Accounts for regulatory burden, digital maturity, competitive pressure, union density, and organizational complexity.

Worker Adaptabilityabsorption
4.5

How well can workers in this group transition to new roles? Composite of net liquid wealth (financial buffer), skill transferability, geographic job density, and age demographics.

Demand Elasticityabsorption
5.0

When AI makes this sector's output cheaper, does demand expand enough to offset job losses? High elasticity means the Jevons Paradox may preserve or even grow employment.

AI Complementarityabsorption
7.5

Is AI primarily enhancing workers in this occupation or replacing them? Based on CFO survey data where available, estimated from task composition and job dimensionality otherwise. Jobs with more distinct task clusters (high dimensionality) tend toward augmentation via the O-Ring "focus effect" — automating some tasks lets workers concentrate on remaining ones, multiplying output quality.

3 task dimensionsMid-range

Task heuristic base: 9.0 -1.5 from dimensionality

Task Composition

How this occupation's work time is distributed across 8 task categories, based on O*NET work activity data.

Information Processing22%
Interpersonal20%
Coordination & Mgmt18%
Analysis & Decision11%
Communication11%
Technical / Specialized9%
Physical / Manual7%
Creative / Generative3%

Top Work Activities

Most important work activities from O*NET, ranked by importance score (1-5).

ActivityCategoryScore
Assisting and Caring for OthersInterpersonal4.92
Communicating with Supervisors, Peers, or SubordinatesCommunication4.56
Resolving Conflicts and Negotiating with OthersInterpersonal4.50
Identifying Objects, Actions, and EventsInformation Processing4.45
Getting InformationInformation Processing4.44
Documenting/Recording InformationTechnical / Specialized4.20
Establishing and Maintaining Interpersonal RelationshipsInterpersonal4.03
Organizing, Planning, and Prioritizing WorkCoordination & Mgmt3.85
Monitoring Processes, Materials, or SurroundingsInformation Processing3.82
Making Decisions and Solving ProblemsAnalysis & Decision3.78

Methodology

This page combines Karpathy's GPT-scored technical exposure (per-occupation) with four additional dimensions inherited from the parent SOC major group: institutional adoption speed, worker adaptability, demand elasticity, and AI complementarity.

Task composition is derived from O*NET work activity data, mapped to 8 internal categories. The complementarity score is adjusted by job dimensionality (Gans & Goldfarb 2024): occupations with more distinct task clusters tend toward augmentation rather than replacement.

Net displacement risk is computed as a weighted composite: exposure (30%), adoption speed (20%), adaptability (15%), demand elasticity (15%), complementarity (20%). Pressure dimensions are normalized independently from absorption dimensions, so defensive factors can fully counterbalance exposure.