publication . Other literature type . Article . 2014

Power to the People: The Role of Humans in Interactive Machine Learning

Saleema Amershi; Maya Cakmak; William Bradley Knox; Todd Kulesza;
Open Access
  • Published: 22 Dec 2014
  • Publisher: Association for the Advancement of Artificial Intelligence (AAAI)
Abstract
<jats:p>Intelligent systems that learn interactively from their end-users are quickly becoming widespread. Until recently, this progress has been fueled mostly by advances in machine learning; however, more and more researchers are realizing the importance of studying users of these systems. In this article we promote this approach and demonstrate how it can result in better user experiences and more effective learning systems. We present a number of case studies that characterize the impact of interactivity, demonstrate ways in which some existing systems fail to account for the user, and explore new ways for learning systems to interact with their users. We ar...
Subjects
free text keywords: Computer Science, Interactive Machine Learning, Computer-Human Interaction, User Interfaces, Machine Learning and Discovery
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