Automotive Service Technicians and Mechanics

Installation, Maintenance, and Repair Occupations
O*NET-SOC コード
49-3023.00

Diagnose, adjust, repair, or overhaul automotive vehicles.

職業名とタスク記述は、公表された英語のまま表示します。ラベル(タスクの種類を含む)は翻訳しています。

AI露出度

  • データ出典: BLS公表時点: 2026-08

    中程度· 相対

    低い4段階の相対区分非常に高い

    職業群単位の値

    尺度・母数・出典

    4段階の相対区分(低い / 中程度 / 高い / 非常に高い)

    BLS雇用見通し表の詳細職業831件が母数。値は NEM(全国雇用マトリクス)コード単位で付与されるため、同じ NEM コードの職業は同じバンドになります

    出典データセット(XLSX ファイルのダウンロード)

  • データ出典: Anthropic公表時点: 2026-03

    0.000

    0.000ここに掲載された値の範囲0.745
    尺度・母数・出典

    観測エクスポージャー指数、公開されたまま0–1

    O*NETタスクへの対応づけが基準

    SOC 2018の職業単位で公表された値で、同じSOC 2018コードを持つO*NET職業はすべてこの値になります

    出典データセット(CSV ファイルのダウンロード)

  • データ出典: ILO公表時点: 2025

    0.18

    0.09ここに掲載された値の範囲0.70

    職業群単位の値

    尺度・母数・出典

    生成AI露出度指数、公開されたまま0–1

    ISCO-08の細分類(4桁)単位で公表された値です。米国労働統計局(BLS)の公式対応表(ISCO-08→2010 SOC、2010 SOC→2018 SOC)を公表どおり適用してこの職業に結び付けており、対応は全部または一部です

    出典データセット(PDF ファイルのダウンロード)

この出典がどのような性格の値か

BLSの区分は絶対水準ではなく相対順位であり、一次測定でもありません。複数の既存研究が付けた職業別パーセンタイル順位を4段階にまとめた値です。雇用や賃金の予測でもなく、導入確率でもなく、自動化と増強を区別しません。

AI 曝露度(OpenAI ルーブリック)

評価済みタスク 30 件 · β ≥ 0.5 のタスク 4 件(13.3%)

β = 直接的な露出(E1)+ 0.5 × ツール利用時の露出(E2)。原典リポジトリの定義に従います。

  • 原典の単位:O*NET 27.2 のタスク → O*NET 31.0 の職業コード
  • 評価済みタスクはすべて O*NET 31.0 のタスク一覧にあります。
出典
OpenAI "GPTs are GPTs" exposure rubric
版
gh-main-0471612
ライセンス
MIT License, Copyright (c) 2024 OpenAI

タスク

O*NET® 31.0 Database のタスク記述です。コアタスクを先に表示します。

タスク種類β(OpenAI)
Test drive vehicles and test components and systems, using equipment such as infrared engine analyzers, compression gauges, and computerized diagnostic devices.コア0
Inspect vehicles for damage and record findings so that necessary repairs can be made.コア0.5
Test and adjust repaired systems to meet manufacturers' performance specifications.コア0
Repair, reline, replace, and adjust brakes.コア0
Review work orders and discuss work with supervisors.コア0
Troubleshoot fuel, ignition, and emissions control systems, using electronic testing equipment.コア0
Confer with customers to obtain descriptions of vehicle problems and to discuss work to be performed and future repair requirements.コア0
Align vehicles' front ends.コア0
Test electronic computer components in automobiles to ensure proper operation.コア0
Tear down, repair, and rebuild faulty assemblies, such as power systems, steering systems, and linkages.コア0
Perform routine and scheduled maintenance services, such as oil changes, lubrications, and tune-ups.コア0
Follow checklists to ensure all important parts are examined, including belts, hoses, steering systems, spark plugs, brake and fuel systems, wheel bearings, and other potentially troublesome areas.コア0
Plan work procedures, using charts, technical manuals, and experience.コア1
Maintain cleanliness of work area.コア0
Align wheels, axles, frames, torsion bars, and steering mechanisms of automobiles, using special alignment equipment and wheel-balancing machines.コア0
Tune automobile engines to ensure proper and efficient functioning.コア0
Repair, replace, or adjust defective fuel injectors, carburetor parts, and gasoline filters.コア0
Repair and service air conditioning, heating, engine cooling, and electrical systems.コア0
Disassemble units and inspect parts for wear, using micrometers, calipers, and gauges.コア0
Change spark plugs, fuel filters, air filters, and batteries in hybrid electric vehicles.コア0
Overhaul or replace carburetors, blowers, generators, distributors, starters, and pumps.コア0
Repair or replace parts such as pistons, rods, gears, valves, and bearings.コア0
Rewire ignition systems, lights, and instrument panels.コア0
Install, adjust, or repair hydraulic or electromagnetic automatic lift mechanisms used to raise and lower automobile windows, seats, and tops.コア0
Diagnose and replace or repair engine management systems or related sensors for flexible fuel vehicles (FFVs) with ignition timing, fuel rate, alcohol concentration, or air-to-fuel ratio malfunctions.コア0
Estimate costs of vehicle repair.補足0.5
Rebuild parts, such as crankshafts and cylinder blocks.補足0
Conduct visual inspections of compressed natural gas fuel systems to identify cracks, gouges, abrasions, discoloration, broken fibers, loose brackets, damaged gaskets, or other problems.補足0.5
Repair or rebuild transmissions.補足0
Retrofit vehicle fuel systems with aftermarket products, such as vapor transfer devices, evaporation control devices, swirlers, lean burn devices, and friction reduction devices, to enhance combustion and fuel efficiency.補足0

職業情報

出典と帰属表示

This page includes information from the O*NET® 31.0 Database (https://www.onetcenter.org/database.html) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. AI Changing Work has modified all or some of this information: the O*NET-SOC code, title and task statements are reproduced in English without change; task-type labels are shown in the page's language and tasks are listed core first; any Korean occupation title shown on the Korean-language page is AI Changing Work's translation; any KSCO-8 unit groups linked to this occupation were paired with it by AI Changing Work's judgment, and the relation labels and statuses are AI Changing Work's additions. USDOL/ETA has not approved, endorsed, or tested these modifications.

Any AI exposure figures on this page are published by third parties, not by AI Changing Work, and none is part of the O*NET information. OpenAI publishes task-level scores (MIT License) for O*NET 27.2 task statements; each is shown next to the O*NET 31.0 task statement with the same task ID, whose wording can differ from the 27.2 statement that was scored. OpenAI also publishes occupation-level scores for O*NET-SOC codes in the same release, and any such score is shown on the O*NET occupation with the same code. Anthropic publishes an observed exposure index in the Anthropic Economic Index (CC-BY), and the U.S. Bureau of Labor Statistics publishes relative AI exposure categories (public domain); both are published per SOC code, and each value is shown on every O*NET occupation with that code. The International Labour Organization publishes a generative AI exposure index in ILO Working Paper 140 (CC BY 4.0) for ISCO-08 unit groups; AI Changing Work links those groups to O*NET occupations by applying the U.S. Bureau of Labor Statistics ISCO-08 to 2010 SOC and 2010 SOC to 2018 SOC crosswalks as published, without case-by-case selection, and these crosswalks match many groups only in part. Where several unit groups are linked, each group's published value is listed, and any summary shows only the lowest and highest of those values with the number of groups; no exposure figure is averaged or recalculated. Any employment figures are published by the U.S. Bureau of Labor Statistics for the SOC group containing this occupation. Each source is credited where its figures are shown.

O*NET OnLine: 49-3023.00 Automotive Service Technicians and Mechanics

KSCO 코드·명칭: 한국표준직업분류(제8차 개정) — 통계청 고시 제2024-328호 (2024-07-01 고시, 2025-01-01 시행). 저작권법 제7조 제2호의 고시 항목이다. 명칭 표기(가운뎃점·띄어쓰기)는 해설서 2차 정오 반영판의 표기를 따랐으며, 고시 항목표와는 18개 명칭에서 가운뎃점 글리프나 띄어쓰기만 다르다. 통계청은 2025년 10월 국가데이터처로 개편되었다. 이 페이지의 KSCO 연결은 통계청·국가데이터처의 공식 연계표가 아니다.

帰属表示とライセンスの全文