Deep-Dial 2019

Report on AAAI 2019 Workshop on Reasoning and Learning for Human-Machine Dialogues (DEEP-DIAL19; Photos)

Natural conversation has been a key sub-area of AI for decades. Their most recent form, chatbots, which can engage people in natural conversation and are easy to build in software, have been in the news a lot lately. There is a mad rush by companies to release chatbots to show their AI capabilities and gain market valuation. However, beyond basic demonstration, there is little experience in how they can be designed and used for real-world applications that need decision making under constraints (e.g., sequential decision making). Furthermore, there is an upcoming interest and need for innovation in Human-Technology-Interaction, as addressed in the context of Companion Technology and Social Robots. Here, the aim is to implement technical systems that smartly adapt their functionality to their users’ individual needs and requirements and are even able to solve problems in close co-operation with human users. To this end, they need to enter into a dialog and convincingly explain their suggestions and decision-making behavior.

To discuss these, the workshop brought together over 100 AI researchers from around the world to discuss a bouquet of research topics around human-machine dialogs. The program included 4 invited talks, 7 reviewed full paper presentations and 4 lightening talks accompanied by posters, and a topical panel discussion.

The event was an exciting day of technical exchange and attendees expressed views that followup workshops will be worthwhile in order to build research momentum around a topic of significant application potential.

Biplav Srivastava, Susanne Biundo, Ullas Nambiar and Imed Zitouni served as cochairs of the workshop.