WASHINGTON—The recent surge in artificial intelligence (AI) developments is already leading to more economic and social benefits, but inadequate data collection in the United States means that some Americans won’t be able to reap those benefits. To avoid exacerbating inequalities perpetuated by inadequate data collection, policymakers should promote more and better data collection, because data is increasingly essential to outcomes in health care, education, and financial services, among other domains, according to a new report from the Center for Data Innovation.
The report recommends a series of policy measures to combat the growing gaps between individuals who are adequately represented in public and private datasets and can use that data productively and those who are not. These gaps form the growing “data divide” in the United States.
“Closing the digital divide has been a top priority for the last decade, but the data divide has mostly been ignored by policymakers,” said Gillian Diebold, a policy analyst with the Center for Data Innovation, who co-authored the report. “Without substantial efforts to increase data representation and access, there will be individuals and communities who are left behind in an increasingly data-driven world.”
In the report, the Center differentiates the data divide from the digital divide, which is the gap between those subscribing to broadband and those not subscribing. The report then explores how policymakers have taken a multi-pronged approach to address the digital divide and recommends they use a similar holistic approach to address the data divide as well.
The report recommends that policymakers take 16 steps to address the data divide. According to the Center, following these steps would lead to touchstones of data equity: data-friendly privacy regulations, a more data-rich economy, enhanced access to data, and better data quality:
- Pass national data privacy legislation that balances privacy and data use.
- Establish standards and best practices for privacy-enhancing technologies.
- Reform federal sectoral privacy laws.
- Invest in smart cities.
- Identify and procure more private-sector data.
- Increase opportunities to share data across organizations and sectors.
- Simplify processes for Americans to donate their data.
- Create datasets for high-value AI use cases.
- Create more sector-specific data portability policies.
- Support open data at state and local levels.
- Provide access to confidential government data with appropriate safeguards.
- Promote data interoperability across federal, state, and local governments.
- Strengthen public-private data standardization practices.
- Pass demographic-specific data protection measures.
- Use synthetic data to fill critical data gaps.
- Routinely maintain government datasets.
“A data-rich society comes with a wealth of benefits—from improved public health to better education. To ensure that all Americans receive these benefits, policymakers should commit to closing the data divide,” said Diebold.