Impact of Argument Type and Concerns in Argumentation with a Chatbot
This work addresses the need for chatbots to effectively persuade users in behavior change tasks, such as promoting exercise, by incorporating argumentation techniques, though it appears incremental in building on existing dialogical methods.
The paper tackled the problem of enabling chatbots to engage in persuasive argumentation by developing methods to acquire arguments, counterarguments, and meta-level information for dialogue decisions. It showed that using these methods in a chatbot made it more persuasive, as evaluated in participant studies.
Conversational agents, also known as chatbots, are versatile tools that have the potential of being used in dialogical argumentation. They could possibly be deployed in tasks such as persuasion for behaviour change (e.g. persuading people to eat more fruit, to take regular exercise, etc.) However, to achieve this, there is a need to develop methods for acquiring appropriate arguments and counterargument that reflect both sides of the discussion. For instance, to persuade someone to do regular exercise, the chatbot needs to know counterarguments that the user might have for not doing exercise. To address this need, we present methods for acquiring arguments and counterarguments, and importantly, meta-level information that can be useful for deciding when arguments can be used during an argumentation dialogue. We evaluate these methods in studies with participants and show how harnessing these methods in a chatbot can make it more persuasive.