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Machine learning and AI are powerful innovations, but are yet to truly change the world due to a fundamental flaw. AI research is too narrowly focused on a limited set of domains relative to its constructive and disruptive effects on individuals, organizations and society as a whole. If a focus on AI social impact seems impossible to maximize without compromising algorithmic efficiency or even profit, that is ultimately a failure to innovate from a technical and social standpoint. By focusing excessively on automation, current AI fails to create new opportunities, while missing out on the potential to improve human productivity, relationships, standards of living, and institutions. However, dystopia is not destiny and AI need not replicate our human biases. By modifying this approach from the ground up while scientifically designing the next-generation of AI around the fundamental question of what it means to be human, not only will we paradoxically make far more efficient AI, but we will inspire an entirely new economic vision for the 21st century

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Kweku Opoku-Agyemang, Ph.D., is former faculty at the University of California, Berkeley in development economics and former computer science researcher at Cornell University. He has advised Google scientists, given talks at Facebook in the US and many others. He believes in a world where the best technologies permeate the global social fabric and are based on our best understanding of the human condition as it evolves. A former session Chair at the Canadian Economic Association, Kweku believes that his next-generation Machine Learning x Doing approach can help organizations and countries to do better by their people. He is based in Toronto, Canada.

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