Artificial General Intelligence and Planetary Justice: A Framework for Safe and Just Transitions

Artificial General Intelligence (AGI) is emerging not only as a technological breakthrough but as a defining challenge for planetary health and global governance. Its potential to accelerate discovery, optimise resource use, and improve health systems is counterbalanced by risks of inequality, domination, and ecological overshoot. This paper introduces a Justice-First Pluralist Framework that embeds fairness, capability expansion, relational equality, procedural legitimacy, and ecological sustainability as constitutive conditions for governing intelligent systems. The framework is realised through a stylised, simulation-based study designed to demonstrate the possibility of formally analysing justice-relevant paradoxes rather than to produce empirically validated results. Three structural paradoxes are examined: (i) efficiency gains that accelerate ecological degradation, (ii) local fairness that externalises global harm, and (iii) coordination that reinforces concentration of power. Monte Carlo ensembles comprising thousands of stochastic runs indicate that justice-compatible trajectories are statistically rare, showing that ethical and sustainable AGI outcomes do not arise spontaneously. The study is conceptual and diagnostic in nature, illustrating how justice can be treated as a feasibility boundary—integrating social equity, ecological limits, and procedural legitimacy—rather than as an after-the-fact correction. Aligning AGI with planetary stewardship therefore requires anticipatory governance, transparent design, and institutional calibration to the safe and just operating space for humanity.

Authors

Institutions

Publication Details

Journal
Challenges
Published
2025-12-08
DOI
https://doi.org/10.3390/challe16040059
Citations
1
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
2.37
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial General Intelligence and Planetary Justice: A Framework for Safe and Just Transitions

Pascal Stiefenhofer, Cafer Deniz
1 citations
Challenges
Ethics and Social Impacts of AI
2.37
article

Artificial General Intelligence and Planetary Justice: A Framework for Safe and Just Transitions

Pascal Stiefenhofer, Cafer Deniz
article en
1 citations

Abstract

Artificial General Intelligence (AGI) is emerging not only as a technological breakthrough but as a defining challenge for planetary health and global governance. Its potential to accelerate discovery, optimise resource use, and improve health systems is counterbalanced by risks of inequality, domination, and ecological overshoot. This paper introduces a Justice-First Pluralist Framework that embeds fairness, capability expansion, relational equality, procedural legitimacy, and ecological sustainability as constitutive conditions for governing intelligent systems. The framework is realised through a stylised, simulation-based study designed to demonstrate the possibility of formally analysing justice-relevant paradoxes rather than to produce empirically validated results. Three structural paradoxes are examined: (i) efficiency gains that accelerate ecological degradation, (ii) local fairness that externalises global harm, and (iii) coordination that reinforces concentration of power. Monte Carlo ensembles comprising thousands of stochastic runs indicate that justice-compatible trajectories are statistically rare, showing that ethical and sustainable AGI outcomes do not arise spontaneously. The study is conceptual and diagnostic in nature, illustrating how justice can be treated as a feasibility boundary—integrating social equity, ecological limits, and procedural legitimacy—rather than as an after-the-fact correction. Aligning AGI with planetary stewardship therefore requires anticipatory governance, transparent design, and institutional calibration to the safe and just operating space for humanity.

ChallengesVol. 16(4)
Royal College of Surgeons in Ireland (IE), Usak University (TR), Newcastle University (GB)
Openalex Percentile: Top 8%
Ethics and Social Impacts of AI
2.37
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.