OpenDP is pleased to announce the first release of DP Wizard, an interactive tool to explore the effect of different parameter choices, and an assistant for implementing those choices with the OpenDP library. DP Wizard builds on what we’ve learned from DP Creator, but offers a simplified development and install process and a streamlined workflow. We would…
How OpenDP and PySyft ensured user privacy for the Christchurch Call report
A recent publication of a comprehensive technical report marking the completion of Phase 1 of the Christchurch Call Initiative on Algorithmic Outcomes (CCIAO) was announced last month which highlights advancements in AI Auditing and safety, allowing external researchers to conduct privacy-preserving audits of production recommender algorithms at LinkedIn and Daily Motion using PySyft and OpenDP….
2024 OpenDP Community Meeting – Recap and Survey
The 2024 OpenDP Community Meeting took place from August 22 to 23 at Harvard University. We joined forces with TPDP again this year, transitioning from the conference to the Community Meeting with an evening reception. Attendees reflected on the busy week of TPDP and greeted newcomers over appetizers and drinks in the Science and Engineering…
Recap: 2024 Interns & Fellows Program
This August, we celebrated another successful year of the OpenDP Interns & Fellows program. We hosted three Visiting Fellows: Damien Aymon from the Swiss Federal Statistical Office; Shlomi Hod from Boston University; and Praneeth Vepakomma from MIT and three interns onsite in Boston: Tudor Cebere from Inria; Gurman Dhaliwal from UC San Diego; and Maxine…
Announcing OpenDP Library 0.11
The OpenDP team is excited to bring you our latest release, OpenDP Library 0.11! The OpenDP Library is a modular collection of algorithms for building privacy-preserving applications, with an extensible approach to tracking privacy, and a vetted implementation. It is available as binaries for Python on PyPI, for R on R-universe, for Rust on crates.io, or in source…
Meet the authors of the newly released book, Hands on Differential Privacy!
Meet the co-authors of the newly released book Hands on Differential Privacy in this 10-minute Q&A with Ethan Cowan (Harvard University), Michael Shoemate (OpenDP/Harvard University), and Mayana Pereira (Microsoft). Moderated by Sharon Ayalde (OpenDP/Harvard University), the co-authors shared their thoughts on why they wrote the book, who would find the most value from it, and how it…
Responsible Use of Differential Privacy: Recap and Next Steps
During the 2023 OpenDP Community Meeting, one of the parallel breakout sessions that was held focused on identifying best practices and choosing applications for DP. Named “Responsible Use of Differential Privacy”, the session was led by Alexandra Wood (Harvard University) and Jayshree Sarathy (Columbia University) who guided the group into an interactive session that discussed ethical frameworks for statistical analysis,…
The Swiss FSO innovates with OpenDP to protect citizen privacy
The Swiss Federal Statistics Office (FSO) published a co-authored blog about our collaborative work to help develop solutions with OpenDP that could be used within the Swiss administration and beyond. …
Announcing the OpenDP Library 0.9
This release features new measurements and transformations, expanded functionality of user-defined primitives, proofs, and R-language bindings. We are continually working on improving the usability and expanding audiences that would benefit from the library. This is a major step in that direction with additional features coming this next quarter. Read more about them below!…
Join the Privacy Attacks & Auditing Working Group!
As part of the 2023 OpenDP Community Meeting, a breakout session centered around privacy attacks and auditing attracted leading experts in the room and online from industry, academia, non-profits, and government entities alike to share their perspectives on this new topic. It was exciting to see broad recognition that attacks are and will continue to…