AI & SOCIETY RESEARCH
Four visions on the future of global governance, AI, and climate change
In this article, we explore the entangled futures of global governance, artificial intelligence (AI), and climate change by developing four scenarios for the year 2045. The aim is not to predict the future, but to expand our imagination of plausible trajectories, while critically examining the political, technological, and environmental interdependencies that shape what lies ahead. Using an interdisciplinary approach grounded in futures studies and scenario analysis, we investigate how governance systems influence, and are influenced by, both AI development and climate responses. We begin by drawing on different academic fields in a conceptual and historical investigation of the three domains, identifying key dynamics and tensions. From this foundation, we construct four narrative scenarios, each articulating a distinct alignment of governance structures, climate pathways, and AI trajectories. Through these fictional-yet-grounded futures, we aim to provoke reflection and debate about which paths might lead to sustainability, justice, and collective flourishing, and which might not. Our contribution lies in the exploration and development of a method for developing and mapping potential future worlds, and using these to evaluate and make use of normative and strategic questions they pose in the present.
Executive Impact: Key Metrics & Insights
Understanding the interplay of global governance, AI, and climate change is critical for strategic planning. This analysis highlights key projections and challenges shaping our collective future.
4
Scenarios for 2045
10 Years
Since Paris Agreement
>4°C
Worst-Case Warming by 2100
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Global Governance in Focus
Our analysis of global governance is rooted in international relations (IR), exploring how various structures impact the provision of global public goods like climate stability and AI safety. We examine four primary forms: anarchical society (anarcho-capitalism) where markets and powerful entities dominate, decentralized norms-based cooperation (English School) emphasizing shared norms, formalized regime-based cooperation (neoliberal institutionalism) focused on rule-based multilateralism, and a centralized supranational authority (world state/cosmopolitan governance). Each presents distinct opportunities and challenges for addressing complex global issues, shaping how collective action can be achieved, or undermined, by free-rider problems and competing interests.
Climate Change Dynamics
Human activity has significantly altered the climate system, leading to urgent calls for global governance. Historically, neoliberal institutionalism has influenced climate governance, exemplified by the IPCC and the UN Framework Convention on Climate Change (UNFCCC), culminating in the Paris Agreement. Despite commitments to limit warming to 1.5°C, this target is increasingly seen as unrealistic. The IPCC outlines several Representative Concentration Pathways (RCPs), ranging from ambitious mitigation (RCP 2.6, stabilizing below 2°C) to worst-case scenarios (RCP 8.5, exceeding 4°C warming). These diverse pathways underscore the critical link between effective global governance and humanity's ability to mitigate and adapt to climate change, including potential geoengineering initiatives.
The Trajectory of Artificial Intelligence
AI, defined as computational systems capable of complex tasks associated with human cognition, is transforming knowledge, culture, and material infrastructures. Influential AI tools are developed by a limited set of actors, embedding specific values and cultural contexts. The current generation of large AI models (e.g., Generative AI) demands immense data and compute power, leading to significant environmental impacts such as increased energy consumption, greenhouse gas emissions, water use, and demand for natural resources. While a widespread "hype bubble" views AI as a solution to many human challenges, concerns remain regarding its longer-term risks, including the "pacing problem" of institutional adaptation to rapid technological change, and the potential for "super-intelligent" systems. This highlights the urgent need for global AI governance to balance innovation with safety and ethical considerations.
Enterprise Process Flow: Scenario Development Methodology
Scope Determination
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Factor Trajectory Analysis
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Narrative Formulation
| Scenario | Global governance | Climate change | Artificial intelligence |
|---|---|---|---|
| 1 | Anarchical society (anarcho-capitalism) | High emissions (RCP 8.5) | Unrestricted acceleration |
| 2 | Decentralized, norms-based cooperation (English school) | Medium emissions (≈ RCP 4.5-6.0) | Restraint |
| 3 | Formalized regime-based cooperation (neoliberal Institutionalism) | Medium emissions (≈ RCP 4.5-6.0) | Rapid acceleration |
| 4 | World state (cosmopolitan governance) | Low emissions (RCP 2.6) | Controlled, intensive use |
Case Study: Scenario 1 - Under a Texan Sun (Anarcho-Capitalism & Unrestricted AI)
In 2045, the world is characterized by an anarchical society where powerful corporations like Neos, led by Charlie, dictate global politics. States have dwindled in influence, their legitimacy eroded by market-driven solutions. Neos, initially a deals-focused company, transformed into a global security corporation by acquiring military AI capabilities, even taking over parts of the US armed forces. Climate change has resulted in high emissions (RCP 8.5), with heatwaves and arid landscapes defining much of the Earth. Neos, leveraging its unrestricted AI acceleration, deploys massive geoengineering projects like "The Climate Resilience Facility" – enclosed biospheres offering stable climates for paying citizens. This approach, while highly profitable, leads to uneven distribution of solutions, increased climate volatility in other regions, and unavoidable migration. Rival corporations, like Alisafe, mobilize against Neos, underscoring a future of widespread destruction and conflict where profit drives even the most radical planetary interventions.
Case Study: Scenario 4 - The Planetary Intelligence Division (World State & Controlled AI)
By 2045, humanity has achieved a world state, led by figures like Nnedi, the first leader of the Planetary Intelligence Division. This elected global body is dedicated to the careful prioritization and coordination of AI projects. The world has moved past severe climate crises and warfare, with New Delhi's skies now clear. Earlier AI-enabled crises and autonomous weapons led to widespread skepticism of uncontrolled AI, culminating in the UN Treaty on the Prohibition of Autonomous Weaponry in 2035. The planetary government implemented and controls technological developments, focusing on controlled, intensive AI use for critical areas. AI infrastructures now primarily serve to expand and strengthen the International Carbon Capture Program. This rigorous governance structure has enabled the world to rapidly approach low emissions (RCP 2.6), leveraging AI for Earth systems modeling and climate tech. Nnedi's vision promotes AI as a tool for life, building a more forgiving and caring world, with a strong focus on mitigating social inequalities and building regenerative infrastructure.
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