Educational Exposure to Generative Artificial Intelligence
Year: 2025
Type: article
Abstract: 1.1 Generative AI Occupational Exposure (AIOE) MeasuresGenerative AI is distinct from prior forms of AI because of its ability to produce new content, and language modeling and image generation capture two key aspects of this. In this note, I use measures of generative AI occupational exposure (AIOE) to image generation and language modeling from Felten et al. (2023). Felten et al. (2021) define language modeling as the "ability to model, predict, or mimic human language" and image generation as the "the creation of complex images." Felten et al. (2021, 2023) constructed the AIOE measures using survey responses of freelance workers from Amazon's Mechanical Turk (mTurk) web service on the relatedness of those applications to 52 occupational abilities from the Department of Labor's Occupational Information Network (O*NET) database. Occupational exposure is then calculated as an average, weighted by the O*NET prevalence and importance scores for each occupation. These AIOE measures are then collapsed from the eight-digit Standard Occupational Classification (SOC) codes to the six-digit SOC codes.
Source: FEDS Notes
Author: Jean Xia Timmerman
Institutions: Federal Reserve, Federal Reserve Board of Governors
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4408014567