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 is announcing several new Responsible ML innovations in Azure Machine Learning that help customers understand, protect, and control their data and models.
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 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.
Visit the Azure blog to learn more.