用于心理健康的AI聊天机器人：来自抑郁症亲身经历的价值与危害
AI Chatbots for Mental Health: Values and Harms from Lived Experiences of Depression
AI总结：
本研究开发了基于GPT-4o的聊天机器人Zenny，通过采访17名抑郁症患者，揭示了信息支持等关键价值，并探讨了心理健康AI聊天机器人的设计建议以平衡支持与风险。
摘要：
LLM的最新进展使聊天机器人能够与用户就各种问题进行互动，包括敏感的心理健康场景。尽管其有效性和可靠性存在不确定性，LLM在这些领域的开发仍在增长，可能导致危害。为了更好地识别和缓解这些危害，了解具有亲身经历的人们的价值观如何与危害相关联至关重要。在本研究中，我们开发了一个技术探针，一个基于GPT-4o的聊天机器人Zenny，使参与者能够参与由先前研究提供的抑郁症自我管理场景。我们使用Zenny采访了17名有抑郁症亲身经历的个体。我们的主题分析揭示了关键价值：信息支持、情感支持、个性化、隐私和危机管理。这项工作探讨了亲身经历价值观、潜在危害以及心理健康AI聊天机器人设计建议之间的关系，旨在增强自我管理支持同时最小化风险。
英文摘要：
Recent advancements in LLMs enable chatbots to interact with individuals on a range of queries, including sensitive mental health contexts. Despite uncertainties about their effectiveness and reliability, the development of LLMs in these areas is growing, potentially leading to harms. To better identify and mitigate these harms, it is critical to understand how the values of people with lived experiences relate to the harms. In this study, we developed a technology probe, a GPT-4o based chatbot called Zenny, enabling participants to engage with depression self-management scenarios informed by previous research. We used Zenny to interview 17 individuals with lived experiences of depression. Our thematic analysis revealed key values: informational support, emotional support, personalization, privacy, and crisis management. This work explores the relationship between lived experience values, potential harms, and design recommendations for mental health AI chatbots, aiming to enhance self-management support while minimizing risks.
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。
