论文标题

聊天机器人的心理健康评估

Mental Health Assessment for the Chatbots

论文作者

Shan, Yong, Zhang, Jinchao, Li, Zekang, Feng, Yang, Zhou, Jie

论文摘要

对话系统评估的先前研究通常集中于聊天机器人产生的质量评估(例如流利,相关性等),即本地和技术指标。对于聊天机器人,响应包括未成年人在内的数百万个在线用户的响应,我们认为它应该具有健康的心理趋势,以避免对他们产生负面的心理影响。在本文中,我们为聊天机器人(抑郁,焦虑,酗酒,同理心)建立了几个心理健康评估维度,并介绍了基于问卷的心理健康评估方法。我们对一些著名的开放域聊天机器人进行评估,发现所有这些聊天机器人都有严重的心理健康问题。我们认为这是由于数据集建设过程中对心理健康风险的忽视和模型培训程序所致。我们希望吸引研究人员对聊天机器人严重的心理健康问题的关注,并提高聊天机器人在积极的情绪互动中的能力。

Previous researches on dialogue system assessment usually focus on the quality evaluation (e.g. fluency, relevance, etc) of responses generated by the chatbots, which are local and technical metrics. For a chatbot which responds to millions of online users including minors, we argue that it should have a healthy mental tendency in order to avoid the negative psychological impact on them. In this paper, we establish several mental health assessment dimensions for chatbots (depression, anxiety, alcohol addiction, empathy) and introduce the questionnaire-based mental health assessment methods. We conduct assessments on some well-known open-domain chatbots and find that there are severe mental health issues for all these chatbots. We consider that it is due to the neglect of the mental health risks during the dataset building and the model training procedures. We expect to attract researchers' attention to the serious mental health problems of chatbots and improve the chatbots' ability in positive emotional interaction.

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