Human-in-the-loop is a model of interaction where a machine process and one or more humans have an iterative interaction. In this paradigm the user has the ability to heavily influence the outcome of the process by providing feedback to the system as well as the opportunity to grab different perspectives about the underlying domain and understand the step by step machine process leading to a certain outcome. Amongst the current major concerns in Artificial Intelligence research are being able to explain and understand the results as well as avoiding bias in the underlying data that might lead to unfair or unethical conclusions. Typically, computers are fast and accurate in processing vast amounts of data. People, however, are creative and bring in their perspectives and interpretation power. Bringing humans and machines together creates a natural symbiosis for accurate interpretation of data at scale. The goal of this workshop is to bring together researchers and practitioners in various areas of AI (i.e., Machine Learning, NLP, Computational Advertising, etc.) to explore new pathways of the humanintheloop paradigm.
The proceedings of the workshop will be published online (open access) and through ACM Digital Library, as a companion volume of The Web Conf. Papers must be submitted in PDF according to the new ACM format published in ACM guidelines, selecting the generic “sigconf” sample. Submissions should not exceed 8 pages including any diagrams or appendices and references. The PDF files must have all non-standard fonts embedded. Submissions must be self-contained and in English. Please submit your contributions to EasyChair and select "Augmenting Intelligence with Humans-in-the-Loop Workshop".
Program Committee (to be completed)