音楽作曲家
芸術・デザイン・エンタメ・メディアAI露出度
- データ出典: BLS公表時点: 2026-08
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
0.037
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
0.28
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73%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
非表示の作業 34 件を表示| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Perform administrative tasks such as applying for grants, developing budgets, negotiating contracts, and designing and printing programs and other promotional materials.27-2041 | 0.040350.1 | 0.008344.1 |
Write changes directly into compositions, or use computer software to make changes.27-2041 | 0.029136.2 | 0.010555.9 |
Rewrite original musical scores in different musical styles by changing rhythms, harmonies, or tempos.27-2041 | 0.00334.1 | —0 |
Arrange music composed by others, changing the music to achieve desired effects.27-2041 | 0.00283.5 | —0 |
Write music for commercial mediums, including advertising jingles or film soundtracks.27-2041 | 0.00263.2 | —0 |
Write musical scores for orchestras, bands, choral groups, or individual instrumentalists or vocalists, using knowledge of music theory and of instrumental and vocal capabilities.27-2041 | 0.00232.8 | —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 |
|---|---|
Study scores to learn the music in detail, and to develop interpretations.O*NET Task ID 22546 | 1.0 |
Apply elements of music theory to create musical and tonal structures, including harmonies and melodies.O*NET Task ID 22547 | 1.0 |
Determine voices, instruments, harmonic structures, rhythms, tempos, and tone balances required to achieve the effects desired in a musical composition.O*NET Task ID 22549 | 1.0 |
Transcribe ideas for musical compositions into musical notation, using instruments, pen and paper, or computers.O*NET Task ID 22551 | 1.0 |
Write musical scores for orchestras, bands, choral groups, or individual instrumentalists or vocalists, using knowledge of music theory and of instrumental and vocal capabilities.O*NET Task ID 22554 | 1.0 |
Fill in details of orchestral sketches, such as adding vocal parts to scores.O*NET Task ID 22559 | 1.0 |
Explore and develop musical ideas based on sources such as imagination or sounds in the environment.O*NET Task ID 22560 | 1.0 |
Write music for commercial mediums, including advertising jingles or film soundtracks.O*NET Task ID 22561 | 1.0 |
Transpose music from one voice or instrument to another to accommodate particular musicians.O*NET Task ID 22562 | 1.0 |
Rewrite original musical scores in different musical styles by changing rhythms, harmonies, or tempos.O*NET Task ID 22563 | 1.0 |
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