Educational Exposure to Generative Artificial Intelligence

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.

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Publication Details

Journal
FEDS Notes
Published
2025-02-01
DOI
https://doi.org/10.17016/2380-7172.3703
Primary Topic
Engineering Education and Technology
Type
article
Field-Weighted Citation Impact
0.00
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article

Educational Exposure to Generative Artificial Intelligence

Jean Xia Timmerman
FEDS Notes
Engineering Education and Technology
article

Educational Exposure to Generative Artificial Intelligence

Jean Xia Timmerman
article en

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.

FEDS Notes(2025-02-26)
Openalex Percentile: Top 96%
Engineering Education and Technology
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