The Statistics of Income (SOI) Division of the Internal Revenue Service collects and curates an enormously valuable trove of tax data, which researchers can use to assess the effects of tax policies and pursue other research questions, such as studying income inequality.
With an increasingly connected world, high-quality datasets can be more easily constructed. Although collecting more and better data can provide great benefits to society, such as furthering medical research or targeting public investments to help those most in need, data privacy concerns surface when that information can be de-anonymized and used maliciously.
The Privacy Research Lab at the Urban Institute is working to develop and promote data collection and analysis methods that safely expand access to confidential data while keeping it just that: confidential. We have partnered with local and federal government agencies and other organizations to apply new data privacy and confidentiality methods so researchers and policymakers can use data to society’s benefit while protecting privacy.
Goal: Our body of work aims to safely expand access to confidential data that advances evidence-based policy-making by creating new ways for researchers to use administrative data while protecting privacy.
Framework: Our work is at the intersection of data privacy and public policy. We are implementing practical privacy-preserving technologies and tools (e.g., synthetic data generation) and exploring the feasibility of state-of-the-art methodologies (e.g., formal privacy) to provide better data access.
Approach: Through Privacy Research Lab, we advance evidence-based public policy decision-making under these four areas:
- Developing and implementing cutting edge privacy-preserving technologies and methodologies (e.g., Safe Data Technologies)
- Collaborating with partner agencies to advance data access (e.g., Allegheny County)
- Applying equity awareness in data privacy methods
- Improving data privacy communications and education