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.
翻译:聊天室在商业和科学环境中越来越普遍,它们帮助客户抱怨产品或服务,或支持客户寻找最佳旅行交易。其他机器人提供心理健康支持或帮助预约医疗预约。本文认为,对用户语言意识形态及其相近期望的洞察力可用于为观众设计机器人语言和互动模式提供信息,并确保公平获得机器人提供的服务。这种论点有三种数据支持:模拟用户与聊天室的互动,为健康预约提供便利,用户对互动的反省评论,用户对与预订室接触后的质量调查评论。在结束发言时,我将界定谈话室AI的受众设计,并讨论如何利用以用户为中心的对聊天室互动和社交语言知情的理论方法的分析,例如关系室管理,支持观众设计。