As state and local governments expand data sharing to improve services, experts warn that privacy, security, and accountability must be prioritized to prevent errors and protect public trust. New guidance outlines key steps for agencies.
State and local governments across the United States are increasingly consolidating and sharing data between agencies to improve service delivery and generate actionable insights. However, new guidance from the Center for Democracy and Technology (CDT) warns that these efforts must be grounded in strong privacy protections and clear accountability to avoid unintended harm to residents.
According to the CDT, as more agencies contribute to shared data systems, the risk of errors and misuse grows. Mistakes in consolidated datasets can lead to serious consequences, such as incorrect denial of benefits, false arrests, or disruptions in government services. These risks can erode public trust and violate the expectations of individuals who provided their data.
Privacy and Security Take Center Stage
The push for greater data sharing comes as federal agencies seek broader access to information held by state and local governments. For example, a 2025 executive order signed by President Donald Trump directed federal agencies to obtain comprehensive data from all state programs receiving federal funding, including data managed by third parties. This move has heightened concerns about data privacy and the potential for overreach.
Recent survey data cited by the CDT found that 74% of Americans are worried about how governments store and use their personal information. The CDT's technical guide urges agencies to carefully consider how data is prepared, protected, and governed before centralizing it, emphasizing that the structure of data sharing-whether through a centralized warehouse or a federated approach-matters less than the safeguards in place.
Key Steps for Agencies
The CDT recommends that agencies establish clear roles and responsibilities for managing shared data. In a warehouse model, one agency typically oversees the maintenance and coordination of the data system. In a federated model, each agency remains responsible for its own data and how it is accessed by others. Formal data sharing agreements can help clarify expectations and outline security measures for all parties involved.
Standardizing data quality, definitions, and matching processes is also critical. Even small inconsistencies, such as differences in how birth dates are formatted, can introduce errors that ripple through shared systems. The CDT suggests agencies develop shared documentation and data matching frameworks to ensure consistency and accuracy. Procedures should also be in place for reporting and correcting errors, especially as data moves further from its original source.
Preparing for AI and Future Technologies
As artificial intelligence tools become more common in government operations, the importance of clean, well-documented data grows. AI can help agencies analyze data to detect fraud or improve program integrity, but it also raises the stakes for data accuracy and privacy. The CDT advises that agencies invest in data cleansing and documentation before deploying AI systems that could influence major decisions affecting residents.
For state and local governments, the challenge is to balance the benefits of data sharing with the need to protect individual privacy and maintain public trust. Careful planning, clear agreements, and ongoing oversight are essential as agencies navigate the evolving landscape of government data consolidation.
Data sharing initiatives are often managed by information technology departments or dedicated data governance teams within state and local agencies. These teams are responsible for implementing technical solutions, drafting agreements, and ensuring compliance with privacy laws. As federal requirements and technology continue to evolve, local governments will need to regularly review and update their data sharing practices to keep pace with new risks and opportunities.
