Statisticiens
Informatique et MathématiquesExposition à l'IA
- Source des données: BLSPublié: 2026-08
Très élevée· relative
FaibleQuatre bandes relativesTrès élevéeValeur par groupe professionnel
Échelle, base et source
Quatre bandes relatives (Faible / Modérée / Élevée / Très élevée)
831 métiers détaillés du tableau des projections d'emploi du BLS. La valeur est attribuée par code de la National Employment Matrix (NEM), si bien que les métiers partageant un code NEM reçoivent la même bande
- Source des données: AnthropicPublié: 2026-03
0.211
0.000Étendue des valeurs présentées ici0.745Échelle, base et source
- Source des données: ILOPublié: 2025
0.56
0.09Étendue des valeurs présentées ici0.70Valeur par groupe professionnel
Échelle, base et source
Indice d'exposition à l'IA générative, 0–1 tel que publié
Groupe de base CITP-08 — tous les métiers partageant le code reçoivent cette valeur
Calculé par ce site, non publié par l'OIT : sur les 1 012 professions que ce site relie au jeu de données de l'OIT, 8% atteignent ou dépassent cette valeur.
Quelle est la nature de la valeur publiée par cette source
La catégorie BLS est un rang relatif et non un niveau absolu, et ce n'est pas une mesure de première main : elle regroupe en quatre bandes les rangs centiles du métier dans plusieurs études publiées. Ce n'est ni une prévision d'emploi ou de salaire, ni une probabilité d'adoption, et elle ne distingue pas automatisation et augmentation.
Task-level exposure
Tâches exposées uniquement| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Report results of statistical analyses, including information in the form of graphs, charts, and tables.15-2041 | 0.070015.2 | 0.01001.0 |
Identify relationships and trends in data, as well as any factors that could affect the results of research.15-2041 | 0.060013.0 | 0.140013.7 |
Design research projects that apply valid scientific techniques, and use information obtained from baselines or historical data to structure uncompromised and efficient analyses.15-2041 | 0.050010.9 | 0.01001.0 |
Write program code to analyze data with statistical analysis software.15-2041 | 0.050010.9 | 0.01001.0 |
Draw conclusions or make predictions, based on data summaries or statistical analyses.15-2041 | 0.04008.7 | 0.220021.6 |
Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.15-2041 | 0.04008.7 | 0.150014.7 |
Plan data collection methods for specific projects, and determine the types and sizes of sample groups to be used.15-2041 | 0.03006.5 | 0.00000.0 |
Evaluate sources of information to determine any limitations, in terms of reliability or usability.15-2041 | 0.02004.3 | 0.390038.2 |
Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering.15-2041 | 0.02004.3 | 0.00000.0 |
Prepare tables and graphs to present clinical data or results.15-2041 | 0.02004.3 | 0.00000.0 |
Collect data through surveys or experimentation.15-2041 | 0.00000.0 | 0.00000.0 |
Analyze archival data, such as birth, death, and disease records.15-2041 | 0.00000.0 | 0.00000.0 |
Analyze clinical or survey data, using statistical approaches such as longitudinal analysis, mixed-effect modeling, logistic regression analyses, and model-building techniques.15-2041 | 0.00000.0 | 0.00000.0 |
Write research proposals or grant applications for submission to external bodies.15-2041 | 0.00000.0 | —0 |
Plan or direct research studies related to life sciences.15-2041 | 0.00000.0 | —0 |
Design surveys to assess health issues.15-2041 | 0.00000.0 | —0 |
Design research studies in collaboration with physicians, life scientists, or other professionals.15-2041 | 0.00000.0 | —0 |
Review clinical or other medical research protocols and recommend appropriate statistical analyses.15-2041 | 0.00000.0 | —0 |
Provide biostatistical consultation to clients or colleagues.15-2041 | 0.00000.0 | —0 |
Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students.15-2041 | 0.00000.0 | —0 |
Prepare and structure data warehouses for storing data.15-2041 | 0.00000.0 | —0 |
| Not observed on any surface — 16 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. | ||
Supervise and provide instructions for workers collecting and tabulating data. | —0 | —0 |
Apply sampling techniques, or use complete enumeration bases to determine and define groups to be surveyed. | —0 | —0 |
Examine theories, such as those of probability and inference, to discover mathematical bases for new or improved methods of obtaining and evaluating numerical data. | —0 | —0 |
Report results of statistical analyses in peer-reviewed papers and technical manuals. | —0 | —0 |
Develop software applications or programming for statistical modeling and graphic analysis. | —0 | —0 |
Teach graduate or continuing education courses or seminars in biostatistics. | —0 | —0 |
Read current literature, attend meetings or conferences, and talk with colleagues to keep abreast of methodological or conceptual developments in fields such as biostatistics, pharmacology, life sciences, and social sciences. | —0 | —0 |
Prepare statistical data for inclusion in reports to data monitoring committees, federal regulatory agencies, managers, or clients. | —0 | —0 |
Prepare articles for publication or presentation at professional conferences. | —0 | —0 |
Calculate sample size requirements for clinical studies. | —0 | —0 |
Determine project plans, timelines, or technical objectives for statistical aspects of biological research studies. | —0 | —0 |
Assign work to biostatistical assistants or programmers. | —0 | —0 |
Monitor clinical trials or experiments to ensure adherence to established procedures or to verify the quality of data collected. | —0 | —0 |
Develop or use mathematical models to track changes in biological phenomena, such as the spread of infectious diseases. | —0 | —0 |
Design or maintain databases of biological data. | —0 | —0 |
Apply research or simulation results to extend biological theory or recommend new research projects. | —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 |
|---|---|
Process large amounts of data for statistical modeling and graphic analysis, using computers.O*NET Task ID 8954 | 1.0 |
Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.O*NET Task ID 8957 | 1.0 |
Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.O*NET Task ID 8958 | 1.0 |
Supervise and provide instructions for workers collecting and tabulating data.O*NET Task ID 8963 | 1.0 |
Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering.O*NET Task ID 8965 | 1.0 |
Develop and test experimental designs, sampling techniques, and analytical methods.O*NET Task ID 8966 | 1.0 |
Examine theories, such as those of probability and inference, to discover mathematical bases for new or improved methods of obtaining and evaluating numerical data.O*NET Task ID 8967 | 1.0 |
Develop software applications or programming for statistical modeling and graphic analysis.O*NET Task ID 20193 | 1.0 |
Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students.O*NET Task ID 20194 | 1.0 |
Determine whether statistical methods are appropriate, based on user needs or research questions of interest.O*NET Task ID 21100 | 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