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.
Cite as: Fung, P. (2021) Ethical and Technological Challenges of Conversational AI. Proc. Interspeech 2021
@inproceedings{fung21_interspeech,
author={Pascale Fung},
title={{Ethical and Technological Challenges of Conversational AI}},
year=2021,
booktitle={Proc. Interspeech 2021}
}