It’s critical that AI systems reflect our values and principles. For organizations developing AI systems at scale, putting principles into practice poses unique challenges. In Azure AI, doing this effectively has required us to innovate across our entire product lifecycle: in our development processes; in the technology that we build; and in the way in which we make technology available. In this talk, I will share our experiences implementing responsible AI at scale across our speech, vision, language, and decision systems.
Sarah’s work focuses on research and emerging technology strategy for AI products in Azure. Sarah works to accelerate the adoption and positive impact of AI by bringing together the latest innovations in research with the best of open source and product expertise to create new tools and technologies.
Sarah is currently leading Responsible AI for the Azure Cognitive Services. Prior to joining the Cognitive Services, Sarah lead the development of responsible AI tools in Azure Machine Learning. She is an active member of the Microsoft AETHER committee, where she works to develop and drive company-wide adoption of responsible AI principles, best practices, and technologies. Sarah was one of the founding researchers in the Microsoft FATE research group and prior to joining Microsoft worked on AI fairness in Facebook.
Sarah is active contributor to the open source ecosystem, she co-founded ONNX, Fairlearn, and OpenDP’s SmartNoise was a leader in the Pytorch 1.0 and InterpretML projects. She was an early member of the machine learning systems research community and has been active in growing and forming the community. She co-founded the MLSys research conference and the Learning Systems workshops. She has a Ph.D. in computer science from UC Berkeley advised by Dave Patterson, Krste Asanovic, and Burton Smith.