But Can You Use It? Design Recommendations for Differentially Private Interactive Systems
December 16, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Liudas Panavas, Joshua Snoke, Erika Tyagi, Claire McKay Bowen, Aaron R. Williams
arXiv ID
2412.11794
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CR,
stat.AP
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Accessing data collected by federal statistical agencies is essential for public policy research and improving evidence-based decision making, such as evaluating the effectiveness of social programs, understanding demographic shifts, or addressing public health challenges. Differentially private interactive systems, or validation servers, can form a crucial part of the data-sharing infrastructure. They may allow researchers to query targeted statistics, providing flexible, efficient access to specific insights, reducing the need for broad data releases and supporting timely, focused research. However, they have not yet been practically implemented. While substantial theoretical work has been conducted on the privacy and accuracy guarantees of differentially private mechanisms, prior efforts have not considered usability as an explicit goal of interactive systems. This work outlines and considers the barriers to developing differentially private interactive systems for informing public policy and offers an alternative way forward. We propose balancing three design considerations: privacy assurance, statistical utility, and system usability, we develop recommendations for making differentially private interactive systems work in practice, we present an example architecture based on these recommendations, and we provide an outline of how to conduct the necessary user-testing. Our work seeks to move the practical development of differentially private interactive systems forward to better aid public policy making and spark future research.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted