Power to the people: The role of humans in interactive machine learning

Machine learning is a powerful tool for transformingdata into computational models that can driveuser-facing applications. However, potential users of such applications, who are often domain experts for the application, have limited involvement in the process of developing them. The intricacies of applying machine-learn-ing techniques to everyday problems have largely restricted their use to skilled practitioners. In the traditional applied machine-learning workflow, these practitioners collect data, select features to represent the data, preprocess and trans-form the data, choose a representation and learning algo-rithm to construct the model, tune parameters of the algo-rithm, and finally assess the quality of the resulting model. This assessment often leads to further iterations on many of the previous steps. Typically, any end-user involvement in this process is mediated by the practitioners and is limited to providing data, answering domain-related questions, or giv