What to Consider When Considering Differential Privacy for Policy

Differential privacy (DP) is a mathematical definition of privacy that can be widely applied when publishing data. DP has been recognized as a potential means of adhering to various privacy-related legal requirements. However, it can be difficult to reason about whether DP may be appropriate for a given context due to tensions that arise when it is brought from theory into practice. To aid policymaking around privacy concerns, we identify three categories of challenges to understanding DP along with associated questions that policymakers can ask about the potential deployment context to anticipate its impacts.

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Publication Details

Journal
Policy Insights from the Behavioral and Brain Sciences
Published
2024-09-17
DOI
https://doi.org/10.1177/23727322241278687
Citations
2
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
0.69
Controls
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article

What to Consider When Considering Differential Privacy for Policy

Priyanka Nanayakkara, Jessica Hullman
2 citations
Policy Insights from the Behavioral and Brain Sciences
Privacy-Preserving Technologies in Data
0.69
article

What to Consider When Considering Differential Privacy for Policy

Priyanka Nanayakkara, Jessica Hullman
article en
2 citations

Abstract

Differential privacy (DP) is a mathematical definition of privacy that can be widely applied when publishing data. DP has been recognized as a potential means of adhering to various privacy-related legal requirements. However, it can be difficult to reason about whether DP may be appropriate for a given context due to tensions that arise when it is brought from theory into practice. To aid policymaking around privacy concerns, we identify three categories of challenges to understanding DP along with associated questions that policymakers can ask about the potential deployment context to anticipate its impacts.

Policy Insights from the Behavioral and Brain SciencesVol. 11(2)
Northwestern University (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 24%
Privacy-Preserving Technologies in Data
0.69
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