Charles H. Bennett, Aram W. Harrow, et al.
IEEE Trans. Inf. Theory
The need to analyse personal data to drive business alongside the requirement to preserve the privacy of data subjects creates a known tension. Data protection regulations such as GDPR and CCPA define strict restrictions and obligations on the collection and processing of personal data. These are also relevant for machine learning models, which can be used to derive personal information about their training sets. The open-source ai-privacy-toolkit is designed to help organizations navigate this challenging area and build more trustworthy AI solutions, with tools that protect privacy and help ensure the compliance of AI models.
Charles H. Bennett, Aram W. Harrow, et al.
IEEE Trans. Inf. Theory
Raymond F. Boyce, Donald D. Chamberlin, et al.
CACM
Kento Tsubouchi, Yosuke Mitsuhashi, et al.
npj Quantum Information
Kaoutar El Maghraoui, Gokul Kandiraju, et al.
WOSP/SIPEW 2010