# Position: AI Must Become Planet-Centered, Not Just Human-Centered

arXiv: https://arxiv.org/abs/2606.13704 · HTML: https://mlsanity.com/paper/2606.13704/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 85 references that are in the map.
- First posted on arXiv 9 Jun 2026.

## Builds on (most cited first, 17 of 17)

- [Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy](https://mlsanity.com/paper/2002.04087/) (2020)
- [The Values Encoded in Machine Learning Research](https://mlsanity.com/paper/2106.15590/) (2021)
- [Principles alone cannot guarantee ethical AI](https://mlsanity.com/paper/1906.06668/) (2019)
- [The Ethics of AI Ethics -- An Evaluation of Guidelines](https://mlsanity.com/paper/1903.03425/) (2019)
- [The role of artificial intelligence in achieving the Sustainable Development Goals](https://mlsanity.com/paper/1905.00501/) (2019)
- [Simulation Intelligence: Towards a New Generation of Scientific Methods](https://mlsanity.com/paper/2112.03235/) (2021)
- [Engagement, User Satisfaction, and the Amplification of Divisive Content on Social Media](https://mlsanity.com/paper/2305.16941/) (2023)
- [Climate-Invariant Machine Learning](https://mlsanity.com/paper/2112.08440/) (2021)
- [Current and Near-Term AI as a Potential Existential Risk Factor](https://mlsanity.com/paper/2209.10604/) (2022)
- [Metaethical Perspectives on 'Benchmarking' AI Ethics](https://mlsanity.com/paper/2204.05151/) (2022)
- [Efficiency is Not Enough: A Critical Perspective of Environmentally Sustainable AI](https://mlsanity.com/paper/2309.02065/) (2023)
- [Collective wind farm operation based on a predictive model increases utility-scale energy production](https://mlsanity.com/paper/2202.06683/) (2022)
- [Crafting Desirable Climate Trajectories with RL Explored Socio-Environmental Simulations](https://mlsanity.com/paper/2410.07287/) (2024)
- [Exploring Equity of Climate Policies using Multi-Agent Multi-Objective Reinforcement Learning](https://mlsanity.com/paper/2505.01115/) (2025)
- [From Prediction to Foresight: The Role of AI in Designing Responsible Futures](https://mlsanity.com/paper/2511.21570/) (2025)
- [Exploring the Viability of the Updated World3 Model for Examining the Impact of Computing on Planetary Boundaries](https://mlsanity.com/paper/2510.07634/) (2025)
- [Expert Assessment: The Systemic Environmental Risks of Artficial Intelligence](https://mlsanity.com/paper/2512.11863/) (2025)

## Abstract (arXiv)

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.