Description

Conversational AI (ConvAI) systems have applications ranging from personal assistance, health assistance to customer services. They have been in place since the first call centre agent went live in the late 1990s. More recently, smart speakers and smartphones are powered with conversational AI with similar architecture as those from the 90s. On the other hand, research on ConvAI systems has made leaps and bounds in recent years with sequence-to-sequence, generation-based models. Thanks to the advent of large scale pre-trained language models, state-of-the-art ConvAI systems can generate surprisingly human-like responses to user queries in open domain conversations, known as chit-chat. However, these generation based ConvAI systems are difficult to control and can lead to inappropriate, biased and sometimes even toxic responses. In addition, unlike previous modular conversational AI systems, it is also challenging to incorporate external knowledge into these models for task-oriented dialog scenarios such as personal assistance and customer services, and to maintain consistency.

With great power comes great responsibility. We must address the many ethical and technical challenges of generation based conversational AI systems to control for bias and safety, consistency, style, knowledge incorporation, etc. In this talk, I will introduce state-of-the-art generation based conversational AI approaches, and will point out remaining challenges of conversational AI and possible directions for future research, including how to mitigate inappropriate responses. I will also present some ethical guidelines that conversational AI systems can follow.