ビデオゲーム開発者
コンピュータ・数学AI露出度
- データ出典: BLS公表時点: 2026-08
非常に高い· 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
- データ出典: Anthropic公表時点: 2026-03
0.288
0.000ここに掲載された値の範囲0.745尺度・母数・出典
- データ出典: ILO公表時点: 2025
0.53
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の職業小分類単位 — 同じコードの職業はすべて同じ値
当サイトの算出であり、ILOが公表した数値ではありません。当サイトがILOデータセットに結び付けた職業1,012件のうち、この値以上のものは14%です。
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。
Task-level exposure
露出のある作業のみ| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Modify existing software to correct errors, allow it to adapt to new hardware, or to improve its performance.15-1132 | 4.158654.0 | 8.655753.7 |
Modify existing software to correct errors, to adapt it to new hardware, or to upgrade interfaces and improve performance.15-1133 | 1.821623.7 | 4.026125.0 |
Analyze user needs and software requirements to determine feasibility of design within time and cost constraints.15-1132 | 0.56717.4 | 1.54469.6 |
Design, develop and modify software systems, using scientific analysis and mathematical models to predict and measure outcome and consequences of design.15-1132 | 0.27803.6 | 0.36022.2 |
Store, retrieve, and manipulate data for analysis of system capabilities and requirements.15-1133 | 0.19012.5 | 0.54373.4 |
Analyze information to determine, recommend, and plan computer specifications and layouts, and peripheral equipment modifications.15-1132 | 0.10491.4 | 0.03640.2 |
Direct software programming and development of documentation.15-1133 | 0.08471.1 | 0.10920.7 |
Consult with customers about software system design and maintenance.15-1132 | 0.08221.1 | 0.00990.1 |
Develop and direct software system testing and validation procedures, programming, and documentation.15-1132 | 0.08031.0 | 0.42872.7 |
Evaluate factors such as reporting formats required, cost constraints, or need for security restrictions to determine hardware configuration.15-1133 | 0.07651.0 | 0.00700.0 |
| Not observed on any surface — 11 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | ||
Coordinate software system installation and monitor equipment functioning to ensure specifications are met. | —0 | —0 |
Supervise the work of programmers, technologists and technicians and other engineering and scientific personnel. | —0 | —0 |
Determine system performance standards. | —0 | —0 |
Train users to use new or modified equipment. | —0 | —0 |
Recommend purchase of equipment to control dust, temperature, and humidity in area of system installation. | —0 | —0 |
Coordinate installation of software system. | —0 | —0 |
Confer with data processing or project managers to obtain information on limitations or capabilities for data processing projects. | —0 | —0 |
Monitor functioning of equipment to ensure system operates in conformance with specifications. | —0 | —0 |
Supervise and assign work to programmers, designers, technologists, technicians, or other engineering or scientific personnel. | —0 | —0 |
Use microcontrollers to develop control signals, implement control algorithms, or measure process variables, such as temperatures, pressures, or positions. | —0 | —0 |
Recommend purchase of equipment to control dust, temperature, or humidity in area of system installation. | —0 | —0 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task | βE1 + 0.5 × E2 |
|---|---|
Analyze information to determine, recommend, and plan installation of a new system or modification of an existing system.O*NET Task ID 21661 | 1.0 |
Analyze user needs and software requirements to determine feasibility of design within time and cost constraints.O*NET Task ID 21662 | 1.0 |
Confer with systems analysts, engineers, programmers and others to design systems and to obtain information on project limitations and capabilities, performance requirements and interfaces.O*NET Task ID 21664 | 1.0 |
Coordinate installation of software system.O*NET Task ID 21666 | 1.0 |
Design, develop and modify software systems, using scientific analysis and mathematical models to predict and measure outcomes and consequences of design.O*NET Task ID 21667 | 1.0 |
Determine system performance standards.O*NET Task ID 21668 | 1.0 |
Develop or direct software system testing or validation procedures, programming, or documentation.O*NET Task ID 21669 | 1.0 |
Modify existing software to correct errors, adapt it to new hardware, or upgrade interfaces and improve performance.O*NET Task ID 21670 | 1.0 |
Monitor functioning of equipment to ensure system operates in conformance with specifications.O*NET Task ID 21671 | 1.0 |
Obtain and evaluate information on factors such as reporting formats required, costs, or security needs to determine hardware configuration.O*NET Task ID 21672 | 1.0 |
Train users to use new or modified equipment.O*NET Task ID 21679 | 0.0 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page
職業情報
この職業に関わる最近の変化
2026年7月: ADP/Stanford linked postings-payroll study of ~7,000 IT workers (2019-2025) prices tasks separately within IT jobs. Advising others on the design or use of technologies is among 8 higher-wage activities; five tasks lost compensation value in 2023-2025 vs 2019-2022, including "develop models of systems, processes, or products." Effect sizes were not published.
[出典: ADP Research / Stanford Digital Economy Lab, Unbundling Jobs (July 2026)]2026年3月: EIG (Mar 2026) argues the weakness in young adults' labor market is about age, not education: young workers of all education levels lag the rest of the labor market, which does not fit the media narrative of AI displacing computer science majors and entry-level graduates.
[出典: EIG: AI and Young-Adult Jobs (March 2026)]2026年3月: Brookings (Mar 2026) says research on AI and the labor market is still in its first inning, and studies disagree: ADP payroll data show employment fell more for young workers in high-AI-exposure occupations, while CPS data show unemployment rose less for workers in more exposed occupations.
[出典: Brookings Institution]These summaries were written by AI Changing Work from the source linked with each one, and any figures in them are given as AI Changing Work summarised them; they can differ from the source's own wording and from figures shown elsewhere on this page, so check the source before relying on them. AI Changing Work matched this page's occupation to an O*NET occupation and chose, by its own judgment, case by case, which summaries relate to that O*NET occupation; a summary appearing here does not mean that its source names this occupation.