जैव सांख्यिकीविद
कंप्यूटर और गणितAI एक्सपोजर
- डेटा स्रोत: BLSप्रकाशन: 2026-08
बहुत उच्च· सापेक्ष
कमचार सापेक्ष श्रेणियाँबहुत उच्चव्यवसाय-समूह स्तर का मान
मापक्रम, आधार और स्रोत
चार सापेक्ष बैंड (कम / मध्यम / उच्च / बहुत उच्च)
BLS रोज़गार पूर्वानुमान तालिका के 831 विस्तृत व्यवसायों के आधार पर। मान NEM (नेशनल एम्प्लॉयमेंट मैट्रिक्स) कोड के स्तर पर दिया जाता है, इसलिए एक ही NEM कोड वाले व्यवसायों को वही बैंड मिलता है
- डेटा स्रोत: Anthropicप्रकाशन: 2026-03
0.211
0.000यहाँ दिए गए मानों की सीमा0.745मापक्रम, आधार और स्रोत
- डेटा स्रोत: ILOप्रकाशन: 2025
0.56
0.09यहाँ दिए गए मानों की सीमा0.70व्यवसाय-समूह स्तर का मान
मापक्रम, आधार और स्रोत
जेनरेटिव AI एक्सपोजर सूचकांक, प्रकाशित रूप में 0–1
ISCO-08 यूनिट समूह — समान कोड वाले सभी व्यवसायों को यही मान मिलता है
यह इस साइट की गणना है, ILO द्वारा प्रकाशित आँकड़ा नहीं: इस साइट द्वारा ILO डेटासेट से जोड़े गए 1,012 व्यवसायों में से 8% इस मान के बराबर या उससे अधिक हैं।
यह स्रोत किस प्रकार का आँकड़ा प्रकाशित करता है
BLS की श्रेणी सापेक्ष रैंक है, निरपेक्ष स्तर नहीं, और यह प्रथम-हस्त माप भी नहीं है: यह कई प्रकाशित अध्ययनों में व्यवसाय की पर्सेंटाइल रैंकों को चार बैंडों में बांटती है। यह रोज़गार या वेतन का पूर्वानुमान नहीं है, न अपनाए जाने की संभावना, और यह स्वचालन और संवर्धन में अंतर नहीं करती।
Task-level exposure
केवल एक्सपोज़र वाले कार्य| Task | Claude.aiRaw / share % |
|---|---|
Evaluate sources of information to determine any limitations in terms of reliability or usability.15-2041 | 0.399527.4 |
Read technical literature and participate in continuing education or professional associations to maintain awareness of current database technology and best practices.15-2041 | 0.13999.6 |
Examine theories, such as those of probability and inference, to discover mathematical bases for new or improved methods of obtaining and evaluating numerical data.15-2041 | 0.09986.8 |
Develop an understanding of fields to which statistical methods are to be applied to determine whether methods and results are appropriate.15-2041 | 0.09396.4 |
Draw conclusions or make predictions based on data summaries or statistical analyses.15-2041 | 0.08375.7 |
Prepare appropriate formatting to data sets as requested.15-2041 | 0.07595.2 |
Report results of statistical analyses, including information in the form of graphs, charts, and tables.15-2041 | 0.07585.2 |
Process large amounts of data for statistical modeling and graphic analysis, using computers.15-2041 | 0.05743.9 |
Identify relationships and trends in data, as well as any factors that could affect the results of research.15-2041 | 0.05343.7 |
Prepare data for processing by organizing information, checking for any inaccuracies, and adjusting and weighting the raw data.15-2041 | 0.05053.5 |
| Not observed on any surface — 28 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. | |
Analyze and interpret statistical data to identify significant differences in relationships among sources of information. | —0 |
Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy. | —0 |
Plan data collection methods for specific projects and determine the types and sizes of sample groups to be used. | —0 |
Supervise and provide instructions for workers collecting and tabulating data. | —0 |
Apply sampling techniques or use complete enumeration bases to determine and define groups to be surveyed. | —0 |
Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering. | —0 |
Teach graduate or continuing education courses or seminars in biostatistics. | —0 |
Prepare statistical data for inclusion in reports to data monitoring committees, federal regulatory agencies, managers, or clients. | —0 |
Calculate sample size requirements for clinical studies. | —0 |
Determine project plans, timelines, or technical objectives for statistical aspects of biological research studies. | —0 |
Assign work to biostatistical assistants or programmers. | —0 |
Plan or direct research studies related to life sciences. | —0 |
Monitor clinical trials or experiments to ensure adherence to established procedures or to verify the quality of data collected. | —0 |
Develop or use mathematical models to track changes in biological phenomena such as the spread of infectious diseases. | —0 |
Design or maintain databases of biological data. | —0 |
Collect data through surveys or experimentation. | —0 |
Analyze archival data such as birth, death, and disease records. | —0 |
Review clinical or other medical research protocols and recommend appropriate statistical analyses. | —0 |
Provide biostatistical consultation to clients or colleagues. | —0 |
Design surveys to assess health issues. | —0 |
Develop technical specifications for data management programming and communicate needs to information technology staff. | —0 |
Write work instruction manuals, data capture guidelines, or standard operating procedures. | —0 |
Track the flow of work forms including in-house data flow or electronic forms transfer. | —0 |
Train staff on technical procedures or software program usage. | —0 |
Supervise the work of data management project staff. | —0 |
Monitor work productivity or quality to ensure compliance with standard operating procedures. | —0 |
Generate data queries based on validation checks or errors and omissions identified during data entry to resolve identified problems. | —0 |
Develop project-specific data management plans that address areas such as data coding, reporting, or transfer, database locks, and work flow processes. | —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 |
|---|---|
Write research proposals or grant applications for submission to external bodies.O*NET Task ID 16241 | 1.0 |
Prepare articles for publication or presentation at professional conferences.O*NET Task ID 16245 | 1.0 |
Calculate sample size requirements for clinical studies.O*NET Task ID 16246 | 1.0 |
Assign work to biostatistical assistants or programmers.O*NET Task ID 16248 | 1.0 |
Write program code to analyze data with statistical analysis software.O*NET Task ID 16249 | 1.0 |
Write detailed analysis plans and descriptions of analyses and findings for research protocols or reports.O*NET Task ID 16250 | 1.0 |
Develop or implement data analysis algorithms.O*NET Task ID 16257 | 1.0 |
Design or maintain databases of biological data.O*NET Task ID 16259 | 1.0 |
Teach graduate or continuing education courses or seminars in biostatistics.O*NET Task ID 16242 | 0.5 |
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.O*NET Task ID 16243 | 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
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[स्रोत: AI Changing Work Blog]