为心理健康福祉负责任地设计AI：AI作为初级保健、营养补充剂或瑜伽导师？
Framing Responsible Design of AI for Mental Well-Being: AI as Primary Care, Nutritional Supplement, or Yoga Instructor?
AI总结：
本文探讨了如何负责任地设计用于心理健康支持的AI工具，通过类比不同角色（如初级保健、营养补充剂或瑜伽导师）来界定其责任和评估标准。
摘要：
如今，数百万人使用非临床的大语言模型（LLM）工具，如ChatGPT，来支持心理健康。本文探讨了如何负责任地设计此类工具，以及如何在设计和评估中实施这种责任。通过采访专家和分析相关法规，我们发现，设计一个LLM工具的责任性涉及：（1）明确其保证的具体益处及其面向的人群。它是否保证特定、已证明的缓解，如非处方药，还是仅提供最小保证，如营养补充剂？（2）指定LLM工具用于改善福祉的“活性成分”以及是否保证其有效交付（如初级保健提供者）或不保证（如瑜伽导师）。这些规范明确了LLM工具的相关风险、适当的评估指标以及LLM开发者、工具设计者和用户各自的责任。这些类比——将LLM工具比作补充剂、药物、瑜伽导师和初级保健提供者——可以为关于其负责任设计的进一步讨论奠定基础。
英文摘要：
Millions of people now use non-clinical Large Language Model (LLM) tools like ChatGPT for mental well-being support. This paper investigates what it means to design such tools responsibly, and how to operationalize that responsibility in their design and evaluation. By interviewing experts and analyzing related regulations, we found that designing an LLM tool responsibly involves: (1) Articulating the specific benefits it guarantees and for whom. Does it guarantee specific, proven relief, like an over-the-counter drug, or offer minimal guarantees, like a nutritional supplement? (2) Specifying the LLM tool's "active ingredients" for improving well-being and whether it guarantees their effective delivery (like a primary care provider) or not (like a yoga instructor). These specifications outline an LLM tool's pertinent risks, appropriate evaluation metrics, and the respective responsibilities of LLM developers, tool designers, and users. These analogies - LLM tools as supplements, drugs, yoga instructors, and primary care providers - can scaffold further conversations about their responsible design.
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。
