In this thesis, I demonstrate how digital inequality is the latest layer in the web of social,cultural, and economic exclusions. Previous research has shown that individual characteristics impact internet and communication technology (ICT) access and adoption. I utilize Van Dijk’s four forms of access to move past the binary of the digital divide. Using the 2019 American Community Survey Public Use Microdata Sample (5 year estimates), I develop two logistic regression models that incorporate individual and community-level factors to predict the likelihood of a resident achieving universal connectivity or being smartphone dependent. The findings indicate that there is a polarity between those who have universal connectivity versus those who are smartphone dependent. Wealthier, more educated residents have the highest rates of obtaining a universal connection. Inversely, residents with lower incomes, with less than a college education are increasingly smartphone dependent.