提出以地球系统为核心的AI新范式，应对全球性危机挑战
Position: AI Must Become Planet-Centered, Not Just Human-Centered
- 将地球视为整体系统，重构AI设计逻辑
- 指出人类中心AI在复杂危机中易加剧系统风险
- 适合关注可持续发展与全球治理的研究者
本文主张当前人工智能范式不足以支持复杂的全球目标，提出以地球为中心的人工智能（PCAI）作为设计哲学与研究议程，将人工智能重新定位为面向行星尺度社会-生态系统的长期演变。该方法基于系统思维，将地球视为一个相互关联的整体，人类是其中的一部分。我们诊断了现有AI框架中普遍存在的局限性，许多仍以人类为中心，在当前由系统性风险、非平稳性和深层不确定性特征的行星条件下，这些局限尤为严重。随后，我们阐述了如何通过强调与全球议程对齐、构建系统感知的AI基础、面向轨迹的评估以及可监测性，重塑从问题定义到模型部署的整个AI生命周期。最后，我们提出一个可验证的主张：若在优化过程中未明确考虑系统性后果，人工智能系统更可能加剧系统性不稳定，而非缓解。
原文摘要 · Abstract (English)
This position paper argues that contemporary AI paradigms are insufficient for supporting complex global goals and introduces Planet-Centered AI (PCAI) as a design philosophy and research agenda that reorients AI toward planetary-scale socio-ecological systems and their long-term trajectories. A planet-centered approach is grounded in systems thinking, treating Earth as an interconnected whole of which humans are part. We diagnose recurring limitations across AI frameworks, many of which remain human-centered, and show why these become especially consequential under current planetary conditions characterized by systemic risk, non-stationarity, and deep uncertainty. We then articulate how PCAI reshapes the AI lifecycle, from problem formulation and model design to evaluation and deployment, by emphasizing alignment with global agendas, developing system-aware AI foundations, trajectory-oriented evaluation, and monitorability. Finally, we advance a falsifiable claim: AI systems optimized without explicit consideration of systemic consequences are more likely to exacerbate systemic instability than to mitigate it.
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