Book

Digital Equity 2.0: How to Close the Data Divide

The United States has strived to address digital inequities in the Internet economy through programs that combat the “digital divide.” But in the data economy, a number of social and economic inequities arise from a lack of data collection

Digital Equity 2.0: How to Close the Data Divide
The United States has strived to address digital inequities in the Internet economy through programs that combat the “digital divide.” But in the data economy, a number of social and economic inequities arise from a lack of data collection or use of data. These inequities—the “data divide”—require new policy solutions to ensure that all Americans are represented in data and can put it to use. To tackle this new challenge, policymakers face two starkly different options: Option A) hold back data collection and data-driven technologies until they are equitable for everyone; or option B) allow the data-driven technologies to prosper while working to increase access for everyone. To close the digital divide, U.S. policymakers have chosen option B. But for the data divide, many are flirting with option A, when they should be choosing option B. INTRODUCTION For the last decade, closing the digital divide, or the gap between those subscribing to broadband and those not subscribing, has been a top priority for policymakers. But high-speed Internet and computing device access are no longer the only barriers to fully participating and benefiting from the digital economy. Data is also increasingly essential, including in health care, financial services, and education. Like the digital divide, a gap has emerged between the data haves and the data have-nots, and this gap has introduced a new set of inequities: the data divide. Policymakers have put a great deal of effort into closing the digital divide, and there is now near-universal acceptance of the notion that obtaining
page1image48286560
CENTER FOR DATA INNOVATION 1
page2image48538352
widespread Internet access generates social and economic benefits. But closing the data divide has received little attention. Moreover, efforts to improve data collection are typically overshadowed by privacy advocates’ warnings against collecting any data. In fact, unlike the digital divide, many ignore the data divide or argue that the way to close it is to collect vastly less data.1 But without substantial efforts to increase data representation and access, certain individuals and communities will be left behind in an increasingly data-driven world. This report describes the multipronged efforts needed to address digital inequity. For the digital divide, policymakers have expanded digital connectivity, increased digital literacy, and improved access to digital devices. For the data divide, policymakers should similarly take a holistic approach, including by balancing privacy and data innovation, increasing data collection efforts across a wide array of fronts, enhancing access to data, improving data quality, and improving data analytics efforts. Applying lessons from the digital divide to this new challenge will help policymakers design effective and efficient policy and create a more equitable and effective data economy for all Americans. The Need for a Data-Rich Society Data leads to better understanding and decision-making among individuals, businesses, and government. Individuals use data to make better decisions about everything from what they buy to how they plan for the future. Businesses use data to find new customers, automate processes, develop and improve products and services, and inform business decisions. Government agencies use data to cut costs, improve social services, and keep citizens safe. A data-rich society brings benefits in a broad range of areas, as shown in Table 1. To ensure all Americans receive these benefits, policymakers should commit to closing the data divide.

Related Books

Cbinsights-State of AI logo

The State of AI Global 2022 recap provides comprehensive data and analysis on dealmaking, funding, and exits by private market AI companies. Some key findings include that global AI funding reached a new high in 2021, with $83.4B invested across 5,064 deals. Additionally, the report highlights the top AI investors and the most active AI acquirers. For more information on the report's findings, please refer to the relevant pages in this PDF file.