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.
All submissions must be written in English. We accept the following formats of submissions:
Two formats are possible for the submission: PDF and HTML. PDF submissions must be formatted according to the information for LNCS Authors (http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0.). We would like to encourage you to submit your paper as HTML, in which case you need to submit a zip archive containing an HTML file and all used resources. If you are new to HTML submission these are good places to start:
In order to check if your HTML submission is compliant with the page limit constraint, please use one of the LNCS layouts and printing/storing it as PDF. Please submit your contributions electronically in PDF or HTML format to EasyChair Accepted papers will be published online via CEUR-WS.