Evaluating the Experience of LGBTQ+ People Using Large Language Model Based Chatbots for Mental Health Support
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866910331331149824 |
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| author | Ma, Zilin Mei, Yiyang Long, Yinru Su, Zhaoyuan Gajos, Krzysztof Z. |
| author_facet | Ma, Zilin Mei, Yiyang Long, Yinru Su, Zhaoyuan Gajos, Krzysztof Z. |
| contents | LGBTQ+ individuals are increasingly turning to chatbots powered by large language models (LLMs) to meet their mental health needs. However, little research has explored whether these chatbots can adequately and safely provide tailored support for this demographic. We interviewed 18 LGBTQ+ and 13 non-LGBTQ+ participants about their experiences with LLM-based chatbots for mental health needs. LGBTQ+ participants relied on these chatbots for mental health support, likely due to an absence of support in real life. Notably, while LLMs offer prompt support, they frequently fall short in grasping the nuances of LGBTQ-specific challenges. Although fine-tuning LLMs to address LGBTQ+ needs can be a step in the right direction, it isn't the panacea. The deeper issue is entrenched in societal discrimination. Consequently, we call on future researchers and designers to look beyond mere technical refinements and advocate for holistic strategies that confront and counteract the societal biases burdening the LGBTQ+ community. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_09260 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Evaluating the Experience of LGBTQ+ People Using Large Language Model Based Chatbots for Mental Health Support Ma, Zilin Mei, Yiyang Long, Yinru Su, Zhaoyuan Gajos, Krzysztof Z. Human-Computer Interaction LGBTQ+ individuals are increasingly turning to chatbots powered by large language models (LLMs) to meet their mental health needs. However, little research has explored whether these chatbots can adequately and safely provide tailored support for this demographic. We interviewed 18 LGBTQ+ and 13 non-LGBTQ+ participants about their experiences with LLM-based chatbots for mental health needs. LGBTQ+ participants relied on these chatbots for mental health support, likely due to an absence of support in real life. Notably, while LLMs offer prompt support, they frequently fall short in grasping the nuances of LGBTQ-specific challenges. Although fine-tuning LLMs to address LGBTQ+ needs can be a step in the right direction, it isn't the panacea. The deeper issue is entrenched in societal discrimination. Consequently, we call on future researchers and designers to look beyond mere technical refinements and advocate for holistic strategies that confront and counteract the societal biases burdening the LGBTQ+ community. |
| title | Evaluating the Experience of LGBTQ+ People Using Large Language Model Based Chatbots for Mental Health Support |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2402.09260 |