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 give the systems democratic legitimacy. Instead, we require processes of deliberation amongst users and other stakeholders on questions about the safety of outputs and deployment contexts. 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：本立場論文呼籲人機互動（HCI）社群專注於設計協商式流程，以指導並協調大型語言模型（LLMs，一種「社會規模技術」）的技術與政策設計。首先，筆者提出社會規模技術的定義，並將LLMs定位於此定義框架中。接著，筆者論證現有確保LLMs安全性的流程有所不足，未能賦予系統民主正當性。取而代之，我們需要在使用者及其他利害關係人之間，針對輸出安全與部署脈絡等問題，進行協商式流程。此一AI安全研究與實踐的轉向，將需要設計企業與公共政策以決定如何實施協商，並設計介面與技術特徵，以將協商結果轉化為技術開發流程。最後，筆者為HCI社群提出角色建議，以確保協商式流程能引導LLMs及其他社會規模技術的技術與政策設計。