The writers address data collection.

POINT: Gillian Diebold

It’s become a popular talking point to list all the risks of data collection, whether it be privacy and surveillance or the lack of transparency that can come with data ownership. But rather than stay bogged down in the potential risks, it’s time to consider how a lack of data collection about some individuals and communities can negatively affect their quality of life.

In today’s digital economy, one significant barrier to opportunity is the data divide, the gaps between the data haves and the data have-nots, and the social and economic inequalities resulting from this lack of data collection and use.

Closing the data divide needs to be a policy priority in the United States to drive robust and equitable growth in the digital economy. Data has become invaluable in today’s economy, where the extent to which individuals and communities can collect data and put it to productive use helps determine everything from health outcomes to public safety and economic growth.

Unfortunately, many have jumped on the bandwagon of criticizing data-driven decision-making as too biased. The truth is that some data-driven services don’t work optimally for some people and groups, especially those from historically underrepresented communities because there is often insufficient data to train these systems. Many of these same critics also argue that data collection is too intrusive, keeping solutions to this problem out of reach. Without prioritizing data equity, the United States will continue to perpetuate digital inequalities and miss out on the opportunity for impactful societal change.

These divides manifest in many ways, from demographic and geographic data gaps to inequitable data systems. That means specific characteristics about your background or where you live determine your ability to benefit from data-driven services and whether the necessary data systems and infrastructure exist.

For example, many Americans have unnecessarily low or inaccurate credit scores due to the data infrastructure for financial services. Credit bureaus often determine someone’s risk and qualification for loans and other services based on information about financial borrowing and repayment history from traditional financial institutions. But this leaves out key forms of “novel” or alternative data, like on-time rent or utility payments, and even information about cash flow in a bank account.

Similarly, older or underfunded health data infrastructure restricts many patients, providers and researchers in their understanding of individual and community health.

American Indians and Alaska Natives continue to be undercounted in federal statistics. This data gap affects federal funding for digital literacy and broadband access on rural and tribal lands. While the Federal Communications Commission and National Telecommunications and Information Administration support programs to bring broadband access to Native lands, government officials lack the necessary data to understand the scope of the issue and often allocate resources ineffectively.

It’s not just that more data will inform better policy. Rather than exacerbating these inequalities and continuing with the status quo, enhancing high-quality data collection and use will empower individuals and communities to better understand themselves and their surroundings and make more informed decisions. Updating infrastructure for environmental data collection will allow more Americans to have accurate, updated information about their surroundings and environmental risk levels, and increasing the availability of longitudinal data systems means students and families can make informed decisions about what type of school will create the best educational outcome. The risk is that some communities have too little data collected about them and are falling behind in the digital economy.

COUNTERPOINT: Spence Purnell

With the increasing digitization of everything from social interaction to shopping to maps and our real-time locations, there are growing calls to regulate technology companies and pass privacy laws mandating how data can be collected. But private data collection during our use of products and everyday services can be done in a way that doesn’t violate consumers’ rights. A willing exchange of goods and services is one of the core forces driving free markets, including today’s technology and demand for personal data.

Before the internet and cellphones existed, consumers willingly exchanged access to their information for services and financial benefits. Shoppers have voluntarily signed up for retail outlet loyalty programs and grocery discount clubs that track purchasing decisions. Consumers don’t have to give up that information but choose to in exchange for lower prices and other benefits. Retailers used the data to learn how to serve and keep customers.

This long-standing practice carried into the digital world with great success. America has become the undisputed home of technological innovation, with firms like Amazon, Apple, Google, Facebook and Netflix all using consumer data to offer better products at lower prices. Apple uses data to improve its devices and services. Netflix uses data on what you watch to improve its recommendations. In countless ways, data has helped technology deliver instant access to millions of websites, products and services via our phones — now powerful pocket computers.

In contrast to today’s loud, bipartisan calls for the government to regulate big tech and pass restrictive privacy laws, one reason so much technological advancement has been possible is the minimal government involvement and burdensome regulations.

Research of data privacy laws — like the Fair Credit Reporting Act, which regulates credit bureaus — finds regulations have led to stagnated industries where only the largest and most politically connected credit bureaus and firms can navigate the costly, complicated regulatory landscape. Rather than helping people, the laws end up hurting consumers by limiting their choices while protecting companies and industries that might otherwise have to produce innovation and better serve customers in the face of competition.

There is a role for the law in consumer data privacy, but for the most part, rather than looking for ways to regulate and punish, states should stay focused on actual consumers’ harms, such as when personally identifiable data is used to commit identity and financial theft. States can also help develop industry standards with groups such as the World World Web Consortium that developed best practices for data and created safe harbors for data companies to assist in keeping data appropriately stored and protected.

Any privacy law should distinguish between personally identifiable data, which would understandably want to be protected in many cases. Consumers should be able to correct or delete sensitive personal information, such as Social Security numbers or other identifying numbers and bank account information. Meanwhile, completely de-identified and anonymized data should not require regulations.