This position paper encourages the Human-Computer Interaction (HCI) community to focus on designing deliberative processes to inform and coordinate technology and policy design for large language models (LLMs) -- a `societal-scale technology'. First, I propose a definition for societal-scale technology and locate LLMs within this definition. Next, I argue that existing processes to ensure the safety of LLMs are insufficient and do not provide the systems with democratic legitimacy. Instead, we require processes of deliberation amongst users and other stakeholders on questions such as: what outputs are safe? and what deployment contexts are safe? This shift in AI safety research and practice will require the design of corporate and public policies that determine how to enact deliberation and the design of interfaces and technical features to translate the outcomes of deliberation into technical development processes. To conclude, I propose roles for the HCI community to ensure deliberative processes inform technology and policy design for LLMs and other societal-scale technology.

翻译：这篇立场论文鼓励人机交互（HCI）社区关注设计审议流程，以指导并协调大型语言模型（LLMs）——这一“社会规模技术”——的技术与政策设计。首先，我提出了社会规模技术的定义，并将LLM置于该定义框架内。接着，我论证现有确保LLM安全的流程不足，未能赋予系统民主合法性。相反，我们需要在用户及其他利益相关者之间就以下问题展开审议：哪些输出是安全的？哪些部署环境是安全的？这一AI安全研究与实践的转变，将要求设计企业和公共政策以决定如何实施审议，并设计界面和技术特性，将审议结果转化为技术开发流程。最后，我提出了HCI社区可以承担的角色，以确保审议流程能够为LLM及其他社会规模技术的技术与政策设计提供信息。