Abstract
This paper explores the area of conversational user interfaces and chatbot development, focusing on the methodological aspects of development. The domain in this paper for chatbot development is healthcare. An increasing issue in chatbot development relates to the difficulty in eliciting specific domain knowledge. As chatbots become more ubiquitous in our daily lives with more complex use cases, the process of eliciting and codifying the domain knowledge has become more complex. This is a problem revisited; in the 1980's, 'expert systems' grew rapidly in popularity and such systems required the same processes of elicitation and codification of human know-how or expertise as we now re-witness in modern chatbot development. A new area of 'knowledge engineering' developed from the expert systems or 'knowledge-based systems' field and from this several knowledge engineering methodologies emerged. The present paper revisits these methodologies and asks if there are lessons to be learned for chatbot design and development from such decades old knowledge engineering methods. The paper presents an amendment to a chatbot methodology, incorporating new stages of 'knowledge gathering' and 'usability testing' into the process.
Highlights
This paper explores the area of conversational user interfaces and chatbot development, focusing on the methodological aspects of development
Chatbots or conversational user interfaces are becoming more prevalent in our daily lives, with bots available to check the weather [12], plan holidays [15] and even talk with a virtual therapist [8]
Before KADS and CommonKADS, knowledge-based systems were developed through trial and error, but there was a clear need for guidelines and techniques to aid the knowledge engineering process [19]
Summary
Chatbots or conversational user interfaces are becoming more prevalent in our daily lives, with bots available to check the weather [12], plan holidays [15] and even talk with a virtual therapist [8]. Facebook Messenger is an example of a platform where the user can interact with bots, and there is no need to switch between multiple apps, reducing the cognitive load for the user [3]. It is easier than ever for users to communicate with chatbots through voice activated devices, with numerous channels for accessing the bot, including Slack, Facebook Messenger, and web channels. Fitzpatrick, Darcy and Vierhile studied the user of chatbots on college students who identify as having symptoms of anxiety and depression [8]. Rizzo et al developed SimCoach, a virtual human support agent that promotes access to psychological healthcare information [14]
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