XAI: Learning Fairness with Interpretable Machine

Event Agenda: 10-min: Trends in Artificial Intelligence and Data Fairness: Tim Denley, Director of Board, Chief Solutions Officer, KPMG Ignition Tokyo A talk on KPMG’s view on data reliability and results along with our effort at KPMG Ignition Tokyo. 30-min: Learning Fairness with Interpretable Machine Learning: Serg Masis, Author of “Interpretable Machine Learning with Python“; Climate & Agronomic Data Scientist, Syngenta An overview of many methods employed to detect and mitigate bias and place guardrails to ensure fairness with Python examples 20-min: Q&A (please submit your questions on ) This event will be moderated by Haiyang Peng, a Senior Scientist at KPMG Ignition Tokyo. Special thanks to KPMG Ignition Tokyo () and Machine Learning Tokyo () for co-hosting the event with us! For anyone who’s interested, our sister company launched a Fairness in AI assessment, now available in