The majority of the progress in AI is centered around designing a single intelligent agent in a centralized warehouse with centralized data. However, this limits the capability of these intelligent systems for a society that is distributed and where data is siloed at multiple scales. I describe a framework where each of us can catalyze progress in AI through a fully decentralized and self-organizing process of collaboration.

Academic, AI, Big Data, Big problems, Cooperation, Machine Learning, Society, Web Abhishek is a 2nd year Ph.D. student at MIT Media Lab. He is interested in the self-organization and decentralization of machine learning algorithms. The central question guiding his research is -- how can we (algorithmically) engineer the principles of self-organization to build anti-fragile systems. He has co-authored multiple papers and built systems in machine learning, data privacy, and distributed computing. Before joining MIT, Abhishek worked with Cisco for 2 years where he did research in AutoML and Machine Learning for systems. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx