Do No Harm Guide: Applying Equity Awareness in Data Privacy Methods

Claire Bowen Speaker
Urban Institute
 
Wednesday, Aug 9: 11:00 AM - 11:25 AM
Invited Paper Session 
Metro Toronto Convention Centre 
Researchers and organizations can increase privacy in datasets through methods such as aggregating, suppressing, or substituting random values. But these means of protecting individuals' information do not always equally affect the groups of people represented in the data. A published dataset might ensure the privacy of people who make up the majority of the dataset but fail to ensure the privacy of those in smaller groups. Or, after undergoing alterations, the data may be more useful for learning about some groups more than others.

In this talk, I will introduce a guide that contains a literature review of equity-focused work in statistical data privacy (SDP) and interviews with nine experts on privacy-preserving methods and data sharing. These experts include researchers and practitioners from academia, government, and industry sectors with diverse technical backgrounds, where we sought to understand both how and to what extent they consider the questions of equity in their work. We also created an illustrative example to highlight potential disparities that can result from applying SDP methods without an equitable workflow.