Conversational Artificial Intelligence (AI) provides a convenient and accessible interface to computing systems. Recently, Conversational AI interfaces have gained popularity through integrated personal assistants such as Amazon Alexa, Google Personal Assistant, Microsoft Cortana, Apple Siri, Facebook Portal, and many others. The shift to integration comes with many challenges and open questions:

- How can conversational agents scale? What are the challenges and solutions?
- What are challenges in using Machine Learning (ML) in conversational agents? What are the best paths forward from rule-based systems toward end-to-end ML conversational agents?
- How can we evaluate conversations given that people have different preferences?
- What are the ethical, societal impacts, and safety concerns of deploying such systems? How can we mitigate such issues?

Novel methods to address or analyze these issues must be developed for widespread and safe development of conversational AI interfaces. Our objective is to provide a platform for disseminating novel methods in Conversational AI research as well as discussing potential issues and solutions for deploying such systems in real world applications. We are interested in expository articles, not technical papers that are accessible to new graduate student or perhaps an industry professional new to the field.

Editors

Asli Celikyilmaz (Microsoft)
Alborz Geramifard (Facebook)
Dilek Hakkani-Tur (Amazon)
Alex Rudnicky (CMU)

Junior Editor
Peter Henderson (Stanford University)