New Responsible ML Tools added to Azure Machine Learning

At Microsoft Build 2020, new Responsible Azure ML Tools and OSS Toolkits were launched.

As organizations look to adopt artificial intelligence (AI), they face significant challenges in developing and using AI responsibly. To help organizations overcome this barrier, Microsoft announced several new Responsible ML innovations in Azure Machine Learning that will help customers understand, protect, and control their data and models.
 
Responsible ML Tools
  • Understand
    New model interpretability and fairness assessment capabilities enable the development of more accurate and fair models.
  • Protect
    New differential privacy computing capabilities enable customers to build machine learning models using sensitive data while safeguarding the privacy of individuals. This is a result of the partnership between Microsoft and Harvard’s Institute for Quantitative School Science, which was announced last September. Additionally, new confidential machine learning capabilities provide a secure and trusted environment for machine learning.
  • Control
    New capabilities for fine-grained traceability, lineage, and access control of data, models, and experiments enable organizations to meet strict regulatory requirements. Additionally, new workflow documentation capabilities to enforce accountability in the machine learning process will be made available to customers shortly after the Build conference.
These new Azure Machine Learning innovations have been built on decades of research and provide organizations with a comprehensive set of capabilities to develop AI solutions responsibly.