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The Cartographer
Position: AI Must Become Planet-Centered, Not Just Human-Centered
June 09, 2026 ยท Grace Period ยท ๐ International Conference on Machine Learning (ICML 2026)
Authors
Maria Perez-Ortiz
arXiv ID
2606.13704
Category
cs.CY: Computers & Society
Cross-listed
cs.AI,
cs.LG
Citations
0
Venue
International Conference on Machine Learning (ICML 2026)
Abstract
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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