Preparing a training course, seminar or any learning experience should be based on the learners’ needs and their interpretation. It is important for a trainer to identify the main ways and methods to identify learners’ needs and to be aware of the importance of doing this process to base the learning intervention on solid foundations. Read More
Preprints are early versions of research articles that have not been peer reviewed. They should not be regarded as conclusive and should not be reported in news media as established information.
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Repair in a task-oriented chatbot, and the question of communication skills for AI
Repair describes the process through which participants in conversation address problems in speaking, understanding, and hearing. In interactions with AI-driven chatbots, repair helps users clarify their intents and addresses problems in understanding intent experienced by chatbots. This paper represents the first attempt to describe repair strategies in a task-oriented text-based chatbot from a user-centred perspective. It is based on the analysis of simulated user interactions with a chatbot facilitating health appointment bookings. The analysis shows that the self-repair strategies which users draw on most frequently (e.g. rephrasing) are not necessarily the ones which prompt the bot to provide relevant responses, whereas more successful self-repair strategies (e.g. restating the intent) tend to be more opaque to users and thus used relatively infrequently. This suggest that the notion of communicative competence needs to be re-thought for conversational AI and that communication skills for AI need to be taught explicitly.
CC BY 4.0