Human Interpretable Machine Learning for Smart Water Management

Explore the intersection of artificial intelligence and water management in this 18-minute conference talk from the Toronto Machine Learning Series. Discover how human interpretable machine learning can address complex challenges facing water supplies worldwide, including aging infrastructure, urbanization, and climate change. Learn about the potential of smart algorithms to leverage IoT data and revolutionize the water industry. Examine the importance of transparent decision-making in water management and its impact on public health, property, and infrastructure. Gain insights into promising approaches for explaining model decisions in environmental modeling, as presented by Naysan Saran, Founder of CANN Forecast. Understand the critical role of human-interpretable AI in building trust and facilitating the adoption of machine learning solutions in the water sector.