Position: AI Must Become Planet-Centered, Not Just Human-Centered
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Computer Science > Computers and Society
Title:Position: AI Must Become Planet-Centered, Not Just Human-Centered
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.
| Subjects: | Computers and Society (cs.CY); Artificial Intelligence (cs.AI); Machine Learning (cs.LG) |
| Cite as: | arXiv:2606.13704 [cs.CY] |
| (or arXiv:2606.13704v1 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2606.13704
arXiv-issued DOI via DataCite
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| Journal reference: | International Conference on Machine Learning (ICML 2026) |
Submission history
From: Maria Perez-Ortiz [view email][v1] Tue, 9 Jun 2026 13:59:15 UTC (4,752 KB)
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