Can Countries Coordinate on AI Safety?

Introduction

Countries can coordinate on AI safety, but so far they have coordinated more successfully on shared principles than on binding rules. Since advanced AI development is global, no single government can fully manage the risks or guarantee that powerful systems are developed safely. International agreements have created important foundations: common language, safety research networks, commitments from leading AI companies, and institutions for scientific assessment. But major gaps remain around enforcement, verification, computing power, geopolitical competition and agreement on what level of risk is acceptable.[GOV.UK]GOV.UKai safety summit 2023 the bletchley declarationAI Safety Summit 2023: The Bletchley Declaration - GOV.UKNovember 1, 2023…Published: November 1, 2023

For an AI-enabled human bloom, this distinction matters. Advanced AI could potentially accelerate scientific discovery, improve health, expand education and help humanity overcome major constraints. Yet these benefits depend partly on whether countries can prevent dangerous competition from pushing development faster than safety knowledge, and whether AI capabilities become a shared global resource rather than a source of concentrated power. International coordination is therefore not only a risk-management question; it is part of the governance challenge of ensuring that increasingly powerful AI supports broad human flourishing.[International AI Safety Report]internationalaisafetyreport.orginternational ai safety report 2025International AI Safety ReportInternational AI Safety Report 2025 | International AI Safety ReportJanuary 29, 2025…Published: January 29, 2025

Why international AI cooperation is difficult

AI safety coordination faces a problem familiar from other strategic technologies: countries may agree that cooperation is valuable while still having incentives to move quickly ahead of rivals. The same AI capabilities that could help discover medicines, improve energy systems or accelerate science could also create economic and geopolitical advantages for states and companies that develop them first.

AI development crosses borders faster than regulation

Traditional regulation often works through national jurisdictions: a government sets rules, companies operating there comply, and regulators enforce standards. Frontier AI is harder because the technology supply chain is international. Research talent, semiconductor manufacturing, cloud computing, data centres and AI models are distributed across multiple countries.

This creates practical coordination questions:

The first International AI Safety Report highlighted that general-purpose AI systems are developing rapidly while scientific understanding of their risks remains incomplete. The report, produced through an international process involving experts nominated by governments and international organisations, aimed to create a shared evidence base rather than a single regulatory solution.[International AI Safety Report]internationalaisafetyreport.orginternational ai safety report 2025International AI Safety ReportInternational AI Safety Report 2025 | International AI Safety ReportJanuary 29, 2025…Published: January 29, 2025

The need for shared evidence is significant because governments cannot coordinate effectively if they disagree about the underlying facts. AI safety debates often involve uncertainty: some researchers emphasise potential catastrophic risks from highly capable systems, while others focus more on immediate harms such as misuse, discrimination, security vulnerabilities and economic disruption. International cooperation requires mechanisms that can accommodate different assessments while still enabling practical action.[International AI Safety Report]internationalaisafetyreport.orginternational ai safety report 2025International AI Safety ReportInternational AI Safety Report 2025 | International AI Safety ReportJanuary 29, 2025…Published: January 29, 2025

Strategic competition creates pressure to move first

The biggest coordination challenge is that AI has characteristics of both a public good and a strategic technology. A safer global AI ecosystem could benefit everyone, but individual countries may fear losing economic influence if they slow development while competitors continue.

This tension resembles earlier technology competitions involving nuclear weapons, biotechnology and advanced computing. However, AI differs because capability improvements can spread quickly through software, models can be copied or adapted, and the same systems may have both beneficial and harmful applications.

Governments therefore face a difficult balance:

The challenge is not solved by assuming either unrestricted acceleration or complete restriction. Effective coordination requires institutions that make safer development compatible with innovation.

How shared safety efforts developed

International AI governance has progressed through several overlapping efforts rather than one global treaty. These initiatives have gradually built a common framework, but most remain based on voluntary commitments, information sharing and cooperation rather than binding enforcement.

From principles to shared testing

One early foundation was the development of international AI principles. The Organisation for Economic Co-operation and Development AI Principles, adopted in 2019 and updated in 2024, became one of the first intergovernmental frameworks for trustworthy AI. They emphasise human-centred values, transparency, accountability, safety and responsible innovation.[oecd.org]oecd.orgA I principles | OECDA I principles | OECD

These principles helped create a common vocabulary, but principles alone do not determine how powerful future systems should be tested, monitored or controlled.

A more focused effort emerged around frontier AI: highly capable models with potentially significant societal impacts. The 2023 AI Safety Summit at Bletchley Park produced the Bletchley Declaration, where participating countries recognised that advanced AI risks require international cooperation and that safe development should accompany efforts to capture AI’s benefits.[GOV.UK]GOV.UKai safety summit 2023 the bletchley declarationAI Safety Summit 2023: The Bletchley Declaration - GOV.UKNovember 1, 2023…Published: November 1, 2023

The summit’s significance was less that it created immediate enforcement mechanisms and more that it established a diplomatic channel between countries with very different interests, including major AI developers and governments.

The Bletchley and Seoul process

The next stage moved from broad agreement towards more specific commitments.

At the 2024 AI Seoul Summit, governments and leading AI organisations developed the Frontier AI Safety Commitments. Companies including major model developers agreed to publish safety frameworks and describe how they would manage severe risks associated with advanced AI systems.[GOV.UK]GOV.UKfrontier ai safety commitments ai seoul summit 2024Frontier AI Safety Commitments, AI Seoul Summit 2024 - GOV.UKMay 21, 2024…Published: May 21, 2024

These commitments represented progress because they encouraged companies to make internal safety approaches more visible. However, they remained voluntary. They did not create a global regulator with the authority to inspect systems, impose penalties or require countries to follow identical standards. Critics have therefore argued that the agreements are useful confidence-building measures but not substitutes for stronger governance.[The Guardian]theguardian.comKey outcomes included the Frontier AI Safety Commitments, signed by 16 companies, promising transparency and accountability in AI develop…

Building scientific cooperation

Another important development has been cooperation around scientific assessment. The International AI Safety Report created a shared review of evidence about advanced AI capabilities and risks, helping governments work from a common understanding rather than isolated national assessments.[International AI Safety Report]internationalaisafetyreport.orginternational ai safety report 2025International AI Safety ReportInternational AI Safety Report 2025 | International AI Safety ReportJanuary 29, 2025…Published: January 29, 2025

This scientific coordination resembles approaches used in other global challenges, where independent expertise helps countries negotiate despite political differences. A shared evidence base does not remove disagreement, but it can make policy discussions more grounded.

Limits of global coordination

The progress of recent years shows that international cooperation is possible. The harder question is whether cooperation can become strong enough to manage increasingly powerful AI systems.

Voluntary agreements have limited enforcement power

Most current AI safety agreements rely on voluntary participation. This has advantages: countries and companies can join quickly, adapt approaches as technology changes and avoid lengthy treaty negotiations. But voluntary systems also create weaknesses.

A company or country may support safety principles while interpreting them differently from others. Governments may struggle to verify whether organisations are meeting commitments. Safety standards may become inconsistent across jurisdictions.

The OECD’s monitoring work on the G7 Hiroshima AI Process illustrates this transition from broad principles towards more measurable accountability. The framework allows companies to report information about risk management practices, incident reporting and safety approaches, helping create more comparable expectations.[oecd.org]oecd.orgOECD launches global framework to monitor application of G7 Hiroshima AI Code of ConductFebruary 7, 2025…Published: February 7, 2025

However, reporting systems are not the same as enforcement. The unresolved question is whether international AI governance will eventually require stronger mechanisms, such as shared evaluation standards, mandatory disclosures or agreements on particularly high-risk capabilities.

Geopolitical divisions complicate cooperation

AI governance is also shaped by competition between major powers. Countries may cooperate on safety research while competing over chips, talent, industrial leadership and military applications.

This creates a difficult environment for agreements. A government may support international safety measures but resist rules that appear to weaken its strategic position. Questions about access to computing resources, export controls and technology sharing are therefore closely linked to AI safety coordination.

The challenge for global governance is avoiding a situation where safety becomes another arena of rivalry. If countries see safety measures only as restrictions imposed by competitors, cooperation becomes harder. If they see safety as infrastructure that protects everyone’s ability to benefit from AI, collaboration becomes more sustainable.

The global benefits question

Coordination gaps are not only about preventing extreme risks. They also affect whether AI’s benefits are distributed widely.

The United Nations’ first AI resolution in 2024 emphasised the need for safe, secure and trustworthy AI systems while addressing digital divides between and within countries. It recognised that developing countries need meaningful access to AI benefits rather than being passive recipients of technology created elsewhere.[United Nations Interactive Platform]unite.un.orgd Nations Interactive PlatformGeneral Assembly Adopts Landmark Resolution on Artificial Intelligence | Office of Information and Com…

This matters for the AI bloom vision because a future of abundance depends on broad participation. Scientific breakthroughs, medical advances and educational tools created by advanced AI will have greater global impact if countries have access to the infrastructure, expertise and institutions needed to use them.

The path from coordination to genuine cooperation

International AI safety agreements have moved the world from almost no shared governance towards a growing network of principles, summits, scientific assessments and voluntary commitments. That is a meaningful change, but it is only an early stage.

The central challenge is moving from agreement on intentions to agreement on practical mechanisms: shared evaluation methods, reliable information exchange, clearer accountability and ways to reduce dangerous incentives in a competitive environment.

For a flourishing AI future, the goal is not simply to slow technology down. It is to create conditions where powerful AI systems can be developed with enough caution, transparency and international trust that their benefits can reach beyond the organisations and countries that build them. The success of global coordination may become one of the defining factors in whether advanced AI expands humanity’s long-term possibilities or creates new concentrations of risk and power.

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Endnotes

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