论文标题
在对话式AI中为受众设计提供案例：融洽的期望和语言意识形态
Making the case for audience design in conversational AI: Rapport expectations and language ideologies in a task-oriented chatbot
论文作者
论文摘要
在商业和科学环境中，聊天机器人越来越普遍。他们帮助客户抱怨产品或服务或支持他们找到最佳旅行交易。其他机器人提供心理健康支持或帮助预定医疗预约。本文认为，可以洞悉用户的语言意识形态及其融洽的期望，可用于告知受众设计机器人的语言和互动模式，并确保公平地访问机器人提供的服务。该论点的基础是三种数据的基础：模拟用户互动与聊天机器人有助于健康约会预订，用户对其交互的内省评论以及用户的定性调查评论在与预订机器人的交战后。最后，我将定义对话式AI的受众设计，并讨论如何以用户为中心的聊天机器人互动和社会语言知情的理论方法（例如融洽的理论管理）来支持受众设计。
Chatbots are more and more prevalent in commercial and science contexts. They help customers complain about a product or service or support them to find the best travel deals. Other bots provide mental health support or help book medical appointments. This paper argues that insights into users' language ideologies and their rapport expectations can be used to inform the audience design of the bot's language and interaction patterns and ensure equitable access to the services provided by bots. The argument is underpinned by three kinds of data: simulated user interactions with a chatbot facilitating health appointment bookings, users' introspective comments on their interactions and users' qualitative survey comments post engagement with the booking bot. In closing, I will define audience design for conversational AI and discuss how user-centred analyses of chatbot interactions and sociolinguistically informed theoretical approaches, such as rapport management, can be used to support audience design.
