Explanations in Interactive Machine Learning

Abstract

This tutorial is intended for Artificial Intelligence researchers and practitioners, as well as domain experts interested in human-in-the-loop machine learning, including interactive recommendation and active learning. The participants will gain an understanding of current developments in interactive machine learning from rich human feedback – with an emphasis on white-box interaction and explanation guided learning – as well as a conceptual map of the variety of methods available and of the relationships between them. The main goal is to inform the audience about the state-of-the-art in explanations for interactive machine learning, open issues and research directions, and how these developments relate to the broader context of machine learning and AI.