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Abstract:
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There are only messy human problems; they only ever have messy human solutions. This is what I’ve learned from my 20+ year career as a computational scientist (who frequently pretends to be an entrepreneur). I’ve built a career...a life around confronting challenges from machine perception of faces to neurotechnologies for Alzheimer's treatment to strategies for reuniting orphan refugees with extended family. In every case, my work was not only deeply grounded in theoretical modeling and machine learning, but also in my often unique perspective on these domains. In my keynote, I will share three personal stories: building an AI to treat my son’s diabetes, exploring the causes for wage gap across companies, and using 122 million data points to identify factors associated with long-term life outcomes. Rather than stories of statistics and technology overcoming profound challenges, each reveals the fundamental role of lived experience and creativity in bringing a messy human solution into the world.
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