Enabling Universal Connectivity via Data-Driven Policymaking: A North American Case Study

Abstract

The lack of universal broadband connectivity is becoming a significant hurdle in today's growing digital world. Despite considerable efforts via numerous grant programs, subsidies, private investments, and research initiatives, the disparity between urban and rural communities continues to widen. The COVID-19 pandemic has further emphasized the importance of affordable high-speed Internet to access many social and economic opportunities including remote work, distance learning, and telemedicine. Nevertheless, with the rise of big data, it is now possible to better understand this digital divide from a data-driven perspective. In this article, we leverage a massive crowd-sourced dataset of smartphone device measurements to extract key insights regarding the current state of the digital divide in North America. Specifically, we quantify the extent of the gap, examine the impact of the COVID-19 pandemic, and explore possible socioeconomic factors that may be influential in operator business models. Finally, we demonstrate how crowdsourced datasets can be leveraged to monitor the impact of emerging technologies, to better direct federal broadband funds, and to make more informed spectrum policy decisions.