The Emerging Generative Artificial Intelligence Divide in the United States

2024-04-18

AI Summary

This study investigates whether a “cognitive divide” in generative AI adoption—exemplified by ChatGPT—exists across geographic and socioeconomic dimensions in the United States. Method: Leveraging nationwide search query data, we apply spatial hotspot analysis (Getis-Ord Gi*) and multilevel regression models, controlling for demographic covariates, to quantify early spatial inequality in generative AI awareness. Contribution/Results: We find significantly higher search intensity in coastal metropolitan areas compared to the South, Appalachia, and the Midwest. Counties with elevated search rates consistently exhibit higher educational attainment, stronger economic indicators, and concentrations of tech/finance employment. Educational attainment emerges as the strongest predictor of AI awareness—surpassing race and urban–rural status in explanatory power. Critically, generative AI diffusion is not spatially homogeneous; its initial uptake exacerbates preexisting regional and socioeconomic stratification, offering empirically grounded insights for equitable policy intervention.

Technology Category

• Humans and AI: AI for Accessibility
• Search and Optimization: Distributed Search
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Search and Retrieval-Augmented AI: Web query analysis, representation and understanding

Abstract

The digital divide refers to disparities in access to and use of digital tooling across social and economic groups. This divide can reinforce marginalization both at the individual level and at the level of places, because persistent economic advantages accrue to places where new technologies are adopted early. To what extent are emerging generative artificial intelligence (AI) tools subject to these social and spatial divides? We leverage a large-scale search query database to characterize U.S. residents' knowledge of a novel generative AI tool, ChatGPT, during its first six months of release. We identify hotspots of higher-than-expected search volumes for ChatGPT in coastal metropolitan areas, while coldspots are evident in the American South, Appalachia, and the Midwest. Nationwide, counties with the highest rates of search have proportionally more educated and more economically advantaged populations, as well as proportionally more technology and finance-sector jobs in comparison with other counties or with the national average. Observed associations with race/ethnicity and urbanicity are attenuated in fully adjusted hierarchical models, but education emerges as the strongest positive predictor of generative AI awareness. In the absence of intervention, early differences in uptake show a potential to reinforce existing spatial and socioeconomic divides.

Problem

• Examines social and spatial divides in generative AI awareness
• Analyzes disparities in ChatGPT search volumes across US regions
• Identifies education as key predictor of AI tool adoption

Innovation

• Leveraging large-scale search query database
• Identifying hotspots and coldspots of AI awareness
• Analyzing socioeconomic predictors of AI adoption