Year: 2025
Type: article
Abstract: Artificial Intelligence (AI) has been repeatedly associated with the potential for automating, or even augmenting, occupational tasks. However, the geographical impact of AI remains unclear. Building on previous work, we employed a deep learning natural language processing model to automatically identify AI patents impacting various occupational tasks. We analyzed a dataset of 17,879 task descriptions and quantified AI’s potential impact at metropolitan statistical areas (MSAs) within the U.S. by examining 24,758 AI patents filed with the United States Patent and Trademark Office (USPTO) between 2015 and 2022. Our findings reveal that MSAs that will be more likely to be impacted by AI are not just hubs of creative industries but will also be characterized by a lack of economic diversity. Indeed, the U.S. MSAs that will be more likely to be impacted are those heavily specialized, with little to no efforts at diversification. These dynamics suggest that AI could amplify existing divides, hitting hardest in areas where economic opportunities are already concentrated in a few sectors, leaving many behind in the race for innovation-driven growth.
Source: EPJ Data Science
Institutions: Nokia (United Kingdom), King's College London
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,890
OpenAlex ID: W4409540206