Can AI be trained to provide financial guidance to low-income individuals and keep them out of burdensome debt? Can it learn patterns of emerging diseases, or discover new ones, before they affect humanity? Can it be used to guide policy decisions around the world to reduce maternal mortality, improve innovation capacity in developing countries, or fight health crises, such as opioid addiction and obesity? Can it learn how nature solves problems with elegance, to inspire more effective and sustainable innovation? These are just a few of the fundamental questions that AI researchers in IBM’s Global Research Labs have begun to tackle.
Drawing from these (and many other) projects conducted under the IBM Science for Social Good umbrella, Aleksandra Mojsilovic illustrates the space of opportunities for AI in addressing the world’s biggest social impact challenges and shares lessons learned from defining and executing these multidisciplinary, multiparty projects. Aleksandra also discusses how and why investing in the AI for Good agenda could enable companies to develop better products and services for their customers.
Aleksandra (Saška) Mojsilovic is a scientist, head of AI foundations at IBM Research, codirector of IBM Science for Social Good, and an IBM fellow. Previously, she was a member of the technical staff at Bell Laboratories. Saška is the author of over 100 publications and holds 16 patents. Her work has been recognized with several awards, including the IEEE Signal Processing Society Young Author Best Paper Award, the INFORMS Wagner Prize, the IBM Extraordinary Accomplishment Award, and the IBM Gerstner Prize. Saška is a fellow of the IEEE and a member of IBM Academy of Technology. She also serves on the board of directors of Neighborhood Trust Financial Partners, which provides financial literacy and economic empowerment training to low-income individuals. Saška holds a PhD in electrical engineering from the University of Belgrade, Serbia.
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