Occupational, industry, and geographic exposure to artificial intelligence: A novel dataset and its potential uses

By Edward W. Felten, Manav Raj, Robert C. Seamans. Strategic Management Journal, 2021

349 citations recorded by the source corpus.

We create and validate a new measure of an occupation’s exposure to AI that we call the AI Occupational Exposure (AIOE). We use the AIOE to construct a measure of AI exposure at the industry level, which we call the AI Industry Exposure (AIIE) and a measure of AI exposure at the county level, which we call the AI Geographic Exposure (AIGE). We also describe several ways in which the AIOE can be used to create firm level measures of AI exposure. We validate the measures and describe how they can be used in different applications by management, organization and strategy scholars.

Subfields: Economics and Econometrics, Management Science and Operations Research, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/a38b2e656c65fdf8e5bf6ca498db54525ad794d7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Manav Raj
2. Edward W. Felten
3. Robert C. Seamans
4. Joana Mendonça
5. Benjamin Meindl
6. Morgan R. Frank

In Management Science and Operations Research

1. Manav Raj
2. Edward W. Felten
3. Robert C. Seamans
4. Joana Mendonça

In Strategy and Management

1. Manav Raj
2. Edward W. Felten
3. Robert C. Seamans
4. Joana Mendonça

Citations in the corpus

• How will Language Modelers like ChatGPT Affect Occupations and Industries? (2023, methodology): “The article specifically builds off and extends the methodology described in Felten et al. (2018, 2021).”
• Exposure of occupations to technologies of the fourth industrial revolution (2021, background): “Accordingly, Felten et al. (2021) describe their exposure score as being forward-looking.”