While many human computation (human-in-the-loop) systems exist in the field of Artificial Intelligence (AI) to solve problems that can't be solved by computers alone, comparatively fewer platforms exist for collecting human knowledge, and evaluation of various techniques for harnessing human insights in improving forecasting models for infectious diseases, such as Influenza and Ebola.

In this thesis, we present the design and implementation of My4Sight, a human computation system developed to harness human insights and intelligence to improve forecasting models. This web-accessible system simplifies the collection of human insights through the careful design of the following two tasks: (i) asking users to rank system-generated forecasts in order of likelihood; and (ii) allowing users to improve upon an existing system-generated prediction. The structured output collected from querying human computers can then be used in building better forecasting models. My4Sight is designed to be a complete end-to- end analytical platform, and provides access to data collection features and statistical tools that are applied to the collected data. The results are communicated to the user, wherever applicable, in the form of visualizations for easier data comprehension. With My4Sight, this thesis makes a valuable contribution to the field of epidemiology by providing the necessary data and infrastructure platform to improve forecasts in real time by harnessing the wisdom of the crowd.