Session: Addressing machine learning issues with Responsible AI
AI is becoming more a part of our lives. We are seeing astonishing innovations in AI that affect us as individuals and members of society. As advancements in AI are rapidly growing, societal expectations are growing as well. There is increasing scrutiny of considering whether AI is trustworthy and whether companies are innovating with people’s concerns in mind. In addition, some industry regulations now require that organizations provide transparency about how their AI systems work. The exciting breakthroughs in AI also expose new challenges.
In this session, we will learn about new practical tools that enable data scientists and companies to continuously transform their machine learning lifecycle to make debugging ML models easier for AI developers, business decision-makers to act faster with more confidence, and end-users to gain more trust. In addition, the session will demonstrate how to use the new Azure Responsible AI dashboard for Error Analysis, Model Comparatively Analysis, Data Analysis, Explainability/Interpretability, Counterfactual/What-If, and Casual analysis to expose issues with fairness, inclusiveness, safety & reliability or transparency. The audience will leave learning best practices of using Azure Responsible AI dashboard to produce AI solutions that are less harmful to society and more trustworthy.
Bio
Ruth Yakubu is a Principal Cloud Advocate at Microsoft. Ruth specializes in Java, Advanced Analytics, Data Platforms and Artificial Intelligence (AI).
In addition, she's been a tech speaker at several conferences like Microsoft Ignite, O'reilly velocity, Devoxx UK, Grace Hopper Dublin, TechSummit, Websummit and numerous other developer conferences. Prior to Microsoft, She has also worked for great companies like UNISYS, ACCENTURE and DIRECTV over the years where she gained a lot of experience with software architectural design and programming. She’s awarded Dzone.com’s Most Valued Blogger.