Abstract
This demonstration paper proposes a hybrid intelligence system that combines the complementary strengths of human and machines for complex decision-making problems that require human “gut feeling” (i.e. success prediction for startups). The architecture extends principles of previous interactive machine learning systems by using continuous input from an expert crowd and explicitly leveraging the advantages of collective intelligence. This approach allows to augment machine learning techniques for generating features, intuitive and analytic labeling as well as troubleshooting.
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