The Emerging Generative Artificial Intelligence Divide in the United States
Madeleine I. G. Daepp, Scott Counts
TL;DR
The paper investigates whether awareness of a major generative AI tool exhibits within-country spatial and socioeconomic divides akin to historical digital divides. It analyzes a large-scale Bing search-log dataset to map ChatGPT awareness across the U.S. during the first six months after release, using spatial clustering metrics ($Moran's I$) and local hotspot analyses ($G^*$) and estimating multilevel negative binomial models with state effects. The findings reveal coastal metropolitan hotspots and southern/Appalachian/rural coldspots, with higher awareness strongly associated with educational attainment, income, and tech-sector presence; after full adjustment, education emerges as the strongest predictor. The study highlights that early disparities in AI awareness could reinforce existing inequalities and emphasizes policy and design interventions to broaden access and education, supported by robustness checks including Google Trends comparisons.
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.