Mental Health Assessment for the Chatbots

TL;DR

This paper proposes a new framework for assessing the mental health of chatbots across multiple dimensions, highlighting potential risks and advocating for improved emotional safety in chatbot development.

Contribution

It introduces mental health assessment dimensions and questionnaire methods for chatbots, revealing prevalent issues in existing models and emphasizing the need for mental health considerations.

Findings

All tested chatbots exhibit severe mental health issues.

Current dataset and training neglect mental health risks.

Assessment framework can identify mental health problems in chatbots.

Abstract

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.