Environmental Slow AI: Design Principles for Generative Systems

环境友好型“慢 AI”：生成式系统的设计原则

Generative AI (genAI) systems produce cultural artefacts at scale, but they also reflect embedded cultural values through their design. Once identified, these values become open to deliberate reshaping. 生成式人工智能（genAI）系统在大规模生产文化制品的同时，也通过其设计反映了内在的文化价值观。一旦这些价值观被识别出来，它们便可以被重新审视并进行有意识的重塑。

This position paper examines the maximalist values of current generative AI through an environmental humanities tradition and proposes design principles in which environmental sustainability serves as the core value instead. 本立场论文通过环境人文学科的视角，审视了当前生成式人工智能的“极简主义”（maximalist）价值观，并提出了一套以环境可持续性为核心价值的设计原则。

The principles are developed under the umbrella of Slow AI, a term that already circulates across several distinct research and practice programs. Five design principles are articulated (restraint, sufficiency, selectivity over retention, material visibility, and friction as affordance), each of them illustrated against the current design of widely deployed systems. 这些原则是在“慢 AI”（Slow AI）的框架下制定的，这一术语目前已在多个不同的研究和实践项目中流传。文中阐述了五项设计原则（克制、适度、选择性优于保留、物质可见性，以及将摩擦力作为一种功能），并结合当前广泛部署的系统设计对每一项原则进行了说明。

Each principle operates at two levels: a design implementation, and an interpretive layer at which users and developers are prompted toward reflective engagement with the system. Together these principles extend human agency by restoring decisions that frictionless defaults have silently removed and do so by building interpretive reflection into design. 每一项原则都在两个层面上发挥作用：一是设计实现层面，二是解释性层面——在该层面，用户和开发者被引导与系统进行反思性互动。这些原则通过恢复那些被“无摩擦”默认设置悄然剥夺的决策权，从而扩展了人类的主体性，并将解释性反思融入到设计之中。