ML for Social Good: Success Stories and Challenges
ML for Social Good: Success Stories and Challenges

Abstract: 

Artificial intelligence, machine learning and deep learning have become hot topics recently due to their overwhelming success in various tasks. Nevertheless, can we go beyond superhuman performance in recognizing objects on image datasets? Are AI and ML already able to bring tangible impact in socially meaningful tasks? United Nation Sustainable Development Goals (UN SDGs) set 17 objectives for peace and prosperity for people and the planet including Climate Action, Good Health and Well-being, and No Poverty. In this tutorial the recent advances in machine learning for social good related to the UN SDGs will be presented. How can machine learning help with disaster relief and environment protection today? Which applications that bring immediate impact are ready to exploit state-of-the-art artificial intelligence methods? What are the challenges in applying machine learning algorithms in the wild? We will discuss these questions in this tutorial.

Bio: 

Olga Isupova received the Specialist (eq. to M.Sc.) degree in applied mathematics and computer science in 2012 from Lomonosov Moscow State University, Moscow, Russia, and the Ph.D. degree in 2017 from the University of Sheffield, Sheffield, U.K. She is a Research Assistant in machine learning with the Department of Engineering Science, University of Oxford, Oxford, U.K. Her research interests include machine learning for disaster response and environment protection, Bayesian nonparametrics, and anomaly detection.

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