AI Privacy Toolkit gets a boost on dataset assessment in latest release
3rd July, 2023
Authors CyberKit4SME and Maya Anderson
IBM’s AI Privacy Toolkit is a set of open-source tools designed to help organizations build more trustworthy AI solutions. It bundles together several practical tools and techniques related to the privacy and compliance of AI models. The toolkit is designed to be used by model developers (like data scientists) as part of their existing ML pipelines. It is implemented as a Python library that can be used with different ML frameworks such as scikit-learn, PyTorch, and Keras.
In addition to the existing ML model anonymization and data minimization modules, AI Privacy Toolkit now also supports privacy risk assessment for synthetic datasets.
Distance based metrics using holdout data.
For details, please see: