Discovering Institutions for Global AI Governance

Introduction:

A new white paper has been released that examines the models and functions of international institutions which could assist in managing the opportunities and risks associated with advanced artificial intelligence (AI). The paper addresses the need for global governance structures to effectively handle the impact of AI on a worldwide scale. It draws on analogies with institutions such as the International Civil Aviation Organisation (ICAO) and the European Organisation for Nuclear Research (CERN) to explore the unique challenges and requirements presented by AI. The research, conducted in collaboration with several universities, investigates how international organizations can help ensure the benefits of AI are accessible to all communities while mitigating potential risks. The paper also emphasizes the crucial role of international and multilateral institutions in addressing issues such as unequal distribution of AI technology and risks associated with powerful AI capabilities. It proposes four potential institutional models aimed at facilitating global coordination and governance functions related to AI. However, the paper acknowledges the operational challenges and uncertainties surrounding these models and calls for further discussions and dialogue among governments and stakeholders to enhance AI governance and coordination. Ultimately, the research encourages the international community to prioritize the development of advanced AI systems for the greater benefit of humanity.

Full News:

New white paper investigates models and functions of international institutions that could help manage opportunities and mitigate risks of advanced AI

Growing awareness of the global impact of advanced artificial intelligence (AI) has inspired public discussions about the need for international governance structures to help manage opportunities and mitigate risks involved.

Many discussions have drawn on analogies with the ICAO (International Civil Aviation Organisation) in civil aviation; CERN (European Organisation for Nuclear Research) in particle physics; IAEA (International Atomic Energy Agency) in nuclear technology; and intergovernmental and multi-stakeholder organisations in many other domains. And yet, while analogies can be a useful start, the technologies emerging from AI will be unlike aviation, particle physics, or nuclear technology.

The critical role of international and multilateral institutions

Access to certain AI technology could greatly enhance prosperity and stability, but the benefits of these technologies may not be evenly distributed or focused on the greatest needs of underrepresented communities or the developing world.

International collaborations could help address these issues by encouraging organisations to develop systems and applications that address the needs of underserved communities, and by ameliorating the education, infrastructure, and economic obstacles to such communities making full use of AI technology.

Additionally, international efforts may be necessary for managing the risks posed by powerful AI capabilities. Without adequate safeguards, some of these capabilities – such as automated software development, chemistry and synthetic biology research, and text and video generation – could be misused to cause harm.

International and multi-stakeholder institutions could help advance AI development and deployment protocols that minimise such risks. For instance, they might facilitate global consensus on the threats that different AI capabilities pose to society, and set international standards around the identification and treatment of models with dangerous capabilities.

Lastly, in situations where states have incentives (e.g. deriving from economic competition) to undercut each other’s regulatory commitments, international institutions may help support and incentivise best practices and even monitor compliance with standards.

Four potential institutional models

We explore four complementary institutional models to support global coordination and governance functions:

• An intergovernmental Commission on Frontier AI could build international consensus on opportunities and risks from advanced AI and how they may be managed. This would increase public awareness and understanding of AI prospects and issues, contribute to a scientifically informed account of AI use and risk mitigation, and be a source of expertise for policymakers.
• An intergovernmental or multi-stakeholder Advanced AI Governance Organisation could help internationalise and align efforts to address global risks from advanced AI systems by setting governance norms and standards and assisting in their implementation. It may also perform compliance monitoring functions for any international governance regime.
• A Frontier AI Collaborative could promote access to advanced AI as an international public-private partnership. In doing so, it would help underserved societies benefit from cutting-edge AI technology and promote international access to AI technology for safety and governance objectives.
• An AI Safety Project could bring together leading researchers and engineers, and provide them with access to computation resources and advanced AI models for research into technical mitigations of AI risks. This would promote AI safety research and development by increasing its scale, resourcing, and coordination.

Operational challenges

Many important open questions around the viability of these institutional models remain. For example, a Commission on Advanced AI will face significant scientific challenges given the extreme uncertainty about AI trajectories and capabilities and the limited scientific research on advanced AI issues to date.

The rapid rate of AI progress and limited capacity in the public sector on frontier AI issues could also make it difficult for an Advanced AI Governance Organisation to set standards that keep up with the risk landscape. The many difficulties of international coordination raise questions about how countries will be incentivised to adopt its standards or accept its monitoring.

Likewise, the many obstacles to societies fully harnessing the benefits from advanced AI systems (and other technologies) may keep a Frontier AI Collaborative from optimising its impact. There may also be a difficult tension to manage between sharing the benefits of AI and preventing the proliferation of dangerous systems.

And for the AI Safety Project, it will be important to carefully consider which elements of safety research are best conducted through collaborations versus the individual efforts of companies. Moreover, a Project could struggle to secure adequate access to the most capable models to conduct safety research from all relevant developers.

Given the immense global opportunities and challenges presented by AI systems on the horizon, greater discussion is needed among governments and other stakeholders about the role of international institutions and how their functions can further AI governance and coordination.

We hope this research contributes to growing conversations within the international community about ways of ensuring advanced AI is developed for the benefit of humanity.

Conclusion:

In conclusion, a new white paper explores the models and functions of international institutions that could help manage the opportunities and risks associated with advanced AI. The paper emphasizes the need for international governance structures to ensure that AI’s benefits are distributed equitably and that risks are mitigated. The role of international and multilateral institutions is seen as critical in addressing issues such as unequal access to AI technology and managing the risks posed by powerful AI capabilities. Four potential institutional models are proposed, including a Commission on Frontier AI, an Advanced AI Governance Organization, a Frontier AI Collaborative, and an AI Safety Project. However, there are operational challenges to consider, such as scientific uncertainties, limited capacity in the public sector, and obstacles to maximizing the benefits of AI. Overall, this research aims to stimulate discussions among governments and stakeholders about the role of international institutions in promoting responsible and beneficial AI development.

Frequently Asked Questions:

1. What is global AI governance?

Global AI governance refers to the establishment of principles, policies, and regulations that guide and oversee the development, deployment, and use of artificial intelligence technologies worldwide. It aims to ensure ethical, responsible, and accountable AI practices to address potential risks and promote the beneficial impact of AI on a global scale.

2. Why is global AI governance important?

Global AI governance is important to address the challenges associated with AI technologies, such as privacy concerns, bias, job displacement, and potential misuse. It helps to establish a framework for collaboration, transparency, and coordination among nations, organizations, and stakeholders to foster innovation, manage risks, and safeguard human rights in the AI era.

3. Who is involved in global AI governance?

Global AI governance involves various stakeholders, including national governments, international organizations, academic institutions, industry leaders, civil society groups, and AI research communities. These entities work together to develop policies, frameworks, and standards that shape the ethical and responsible use of AI technologies globally.

4. What are the key institutions exploring global AI governance?

There are several key institutions actively exploring global AI governance, including the United Nations (UN), the Global Partnership on Artificial Intelligence (GPAI), the Organisation for Economic Co-operation and Development (OECD), the World Economic Forum (WEF), and various AI research organizations and think tanks.

5. How do these institutions contribute to global AI governance?

These institutions contribute to global AI governance by facilitating international dialogues, conducting research, developing guidelines, and proposing policy recommendations. They work towards fostering collaboration, identifying best practices, and promoting principles that ensure the responsible and sustainable development and deployment of AI technologies globally.

6. What are the main challenges in global AI governance?

The main challenges in global AI governance include ensuring fairness and avoiding bias in AI algorithms, protecting privacy and personal data, addressing job displacement caused by automation, managing AI-related cybersecurity risks, and ensuring accountability and transparency in AI decision-making processes.

7. How can global AI governance benefit society?

Global AI governance can benefit society by promoting ethical and responsible AI practices. It helps to minimize the risks associated with AI technologies, protect individual rights and privacy, foster trust in AI systems, ensure fairness and non-discrimination, and harness AI’s potential for social and economic development.

8. Are there any international agreements or treaties on global AI governance?

Currently, there are no specific international agreements or treaties solely focused on global AI governance. However, various initiatives and frameworks have been developed to guide AI governance, such as the OECD Principles on Artificial Intelligence and the AI Ethics Guidelines of the European Commission.

9. How can individuals contribute to global AI governance?

Individuals can contribute to global AI governance by staying informed about AI advancements, engaging in public discussions on AI ethics and policy, supporting initiatives that promote responsible AI development, advocating for transparency and accountability in AI systems, and participating in relevant forums and consultations.

10. Is global AI governance a one-size-fits-all approach?

No, global AI governance is not a one-size-fits-all approach. While there are overarching principles and common challenges that need to be addressed globally, different countries and regions may have specific cultural, societal, and legal considerations. It is important to foster collaboration while respecting diversity and allowing for context-specific adaptations in AI governance frameworks.