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arXiv 2201.05382cs.CLcs.HC

Mental Health Assessment for the Chatbots

Pattern Recognition Center, WeChat AI, Tencent Inc(腾讯公司微信人工智能模式识别中心);University of Chinese Academy of Sciences(中国科学院大学)

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

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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