Art Appraisers
Arts, Design, Entertainment & MediaUnited States · BLS Employment Projections 2025–35: this SOC code is not among the published items.
AI exposure
- Data source: AnthropicPublished: 2026-03
0.220
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.45
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
ISCO-08 unit group — every occupation sharing the code gets this value
Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 25% score at or above this value.
- Data source: OpenAIPublished: 2023
0.662
0.000Range of values carried here0.844Scale, basis and source
Task-level exposure
Show 48 hidden tasks| Task | Claude.aiRaw / share % |
|---|---|
Interpret results of financial analysis procedures.13-2099 | 0.119014.8 |
Research or develop analytical tools to address issues such as portfolio construction or optimization, performance measurement, attribution, profit and loss measurement, or pricing models.13-2099 | 0.103812.9 |
Apply mathematical or statistical techniques to address practical issues in finance, such as derivative valuation, securities trading, risk management, or financial market regulation.13-2099 | 0.07669.5 |
Analyze financial or operational performance of companies facing financial difficulties to identify or recommend remedies.13-2099 | 0.06197.7 |
Develop or implement risk-assessment models or methodologies.13-2099 | 0.04605.7 |
Structure or negotiate deals, such as corporate mergers, sales, or acquisitions.13-2099 | 0.04425.5 |
Employ financial models to develop solutions to financial problems or to assess the financial or capital impact of transactions.13-2099 | 0.03053.8 |
Produce written summary reports of financial research results.13-2099 | 0.02793.5 |
Identify, track, or maintain metrics for trading system operations.13-2099 | 0.02713.4 |
Define or recommend model specifications or data collection methods.13-2099 | 0.02593.2 |
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 |
|---|---|
Prepare requirements documentation for use by software developers.O*NET Task ID 15982 | 1.0 |
Collaborate in the development or testing of new analytical software to ensure compliance with user requirements, specifications, or scope.O*NET Task ID 15985 | 1.0 |
Maintain or modify all financial analytic models in use.O*NET Task ID 15987 | 1.0 |
Produce written summary reports of financial research results.O*NET Task ID 15988 | 1.0 |
Develop core analytical capabilities or model libraries, using advanced statistical, quantitative, or econometric techniques.O*NET Task ID 15990 | 1.0 |
Devise or apply independent models or tools to help verify results of analytical systems.O*NET Task ID 15996 | 1.0 |
Apply mathematical or statistical techniques to address practical issues in finance, such as derivative valuation, securities trading, risk management, or financial market regulation.O*NET Task ID 15997 | 1.0 |
Provide application or analytical support to researchers or traders on issues such as valuations or data.O*NET Task ID 15983 | 0.5 |
Identify, track, or maintain metrics for trading system operations.O*NET Task ID 15984 | 0.5 |
Research new financial products or analytics to determine their usefulness.O*NET Task ID 15986 | 0.5 |
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