Bioinformatics Scientists
Life, Physical & Social SciencesAI exposure
- Data source: BLSPublished: 2026-08
Very high· relative
LowFour relative bandsVery highGroup-level value
Scale, basis and source
Four relative bands (Low / Moderate / High / Very high)
831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band
- Data source: AnthropicPublished: 2026-03
0.479
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.40
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, 39% score at or above this value.
What kind of figure this source publishes
The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.
Task-level exposure
Exposed tasks only| Task | Claude.aiRaw / share % |
|---|---|
Process data for analysis, using computers.15-2091 | 0.097253.1 |
Translate data into numbers, equations, flow charts, graphs, or other forms.15-2091 | 0.084046.0 |
Apply standardized mathematical formulas, principles, and methodology to the solution of technological problems involving engineering or physical science.15-2091 | 0.00160.9 |
| Not observed on any surface — 3 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. | |
Reduce raw data to meaningful terms, using the most practical and accurate combination and sequence of computational methods. | —0 |
Confer with scientific or engineering personnel to plan projects. | —0 |
Modify standard formulas so that they conform to project needs and data processing methods. | —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 |
|---|---|
Develop or maintain applications that process biologically based data into searchable databases for purposes of analysis, calculation, or presentation.O*NET Task ID 17706 | 1.0 |
Monitor database performance and perform any necessary maintenance, upgrades, or repairs.O*NET Task ID 17708 | 1.0 |
Analyze or manipulate bioinformatics data using software packages, statistical applications, or data mining techniques.O*NET Task ID 17709 | 1.0 |
Create data management or error-checking procedures and user manuals.O*NET Task ID 17711 | 1.0 |
Design or implement web-based tools for querying large-scale biological databases.O*NET Task ID 17712 | 1.0 |
Develop or apply data mining and machine learning algorithms.O*NET Task ID 17713 | 1.0 |
Document all database changes, modifications, or problems.O*NET Task ID 17714 | 1.0 |
Extend existing software programs, web-based interactive tools, or database queries as sequence management and analysis needs evolve.O*NET Task ID 17715 | 1.0 |
Participate in the preparation of reports or scientific publications.O*NET Task ID 17717 | 1.0 |
Test new or updated software or tools and provide feedback to developers.O*NET Task ID 17718 | 1.0 |
Confer with database users about project timelines and changes.O*NET Task ID 17722 | 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