How to debug and mitigate machine learning model issues using error analysis, fairness assessment and interpretability


Data scientists and AI developers often need to use various tools to holistically evaluate their models and data. For example: they might have to use model interpretability and fairness assessment together, which can be tedious. 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 and areas where machine learning models continue to miss expectations.

This session will demonstrate new practical tools that enable data scientists and companies to continuously transform their Machine Learning life cycles to make debugging models simpler for AI developers; business decision-makers to act faster with more confidence; and end-users gain trust in AI system. In addition, the session will illustrate how to use the new Azure Responsible AI dashboard to perform Error Analysis, Data Analysis, Model Overview and Fairness Assessment. These tools enable machine learning professionals to debug their model to improve its performance to be more fair, inclusive, safe & reliable, and transparent. The audience will leave learning the best practices of using the open-source Responsible AI Toolbox components to produce AI systems that are less harmful to society and more trustworthy.


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’s Most Valued Blogger.

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