Enabling responsible development of artificial intelligent technologies is one of the major challenges we face as the field moves from research to practice. Researchers and practitioners from different disciplines have highlighted the ethical and legal challenges posed by the use of machine learning in many current and future real-world applications. Now there are calls from across the industry (academia, government, and industry leaders) for technology creators to ensure that AI is used only in ways that benefit people and “to engineer responsibility into the very fabric of the technology.” Overcoming these challenges and enabling responsible development is essential to ensure a future where AI and machine learning can be widely used. In this talk we will cover two of our open source toolkits InterpretML and Fairlearn. We will discuss their integration with the Azure Machine Learning platform, share lessons learned and future steps.
Mehrnoosh Sameki is a senior technical program manager at Microsoft, responsible for leading the product efforts on machine learning interpretability and fairness open source packages, InterpretML and Fairlearn and their integration within the Azure Machine Learning platform. Previously, she was a data scientist at Rue Gilt Groupe, incorporating data science and machine learning in the retail space to drive revenue and enhance customers’ personalized shopping experiences. She earned her PhD degree in computer science at Boston University, advised by professor Betke.