AI for All? Unpacking Digital Inequalities in the AI Era

• In Event: 50462 - Section on Science, Knowledge, and Technology Roundtables
  In Refereed Roundtable (60 minute): Table 1: SKAT approaches to AI

Abstract

This study investigates the evolving nature of digital inequalities in the era of AI, focusing on the intersection of digital literacy, access, and user perceptions. While the digital divide has long been a concern in education, the rapid adoption of AI tools like ChatGPT raises new questions about how these technologies may exacerbate or mitigate existing disparities. Contrary to assumptions that younger generations are inherently tech-savvy, research shows that digital skills are unevenly distributed and often tied to socio-economic status (van Dijk 2020; Helsper 2021). This research addresses two key questions: 1) How do digital literacy and access to technology shape engagement with generative AI tools? and 2) What are the perceptions and self-perceptions of users regarding their AI-related digital literacy skills? Using a quantitative approach, we analyze survey data measuring digital literacy, access, usage patterns, attitudes toward AI, and socio-economic variables. Multivariate regression or Structural Equation Modeling (SEM) will be employed to examine the key factors contributing to digital disparities.

This research is significant for its interdisciplinary approach, bridging sociology, education, and human-computer interaction to explore how generative AI influences digital inequalities. By focusing on socio-economic factors and user perceptions, the findings will inform policies and practices that facilitate more effective engagement with emerging technologies, preparing society for the challenges and opportunities of the AI era. Ultimately, this study aims to advance our understanding of digital disparities and contribute to creating a better-prepared society for the future.

Authors

• Yi Yin, Utah Valley University

• Joni Hayward Marcum, Utah Valley University