Options and Motivations for International AI Benefit Sharing

This is a summary of “Options and Motivations for International Benefit Sharing,” a new GovAI Report by Claire Dennis, Sam Manning, Stephen Clare, Boxi Wu, Jake Okechukwu Effoduh, Chinasa T. Okolo, Lennart Heim, and Katya Klinova.

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GovAI research blog posts represent the views of their authors rather than the views of the organisation.

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Introduction

Advanced AI systems could generate substantial societal benefits through faster economic growth and scientific progress. But these benefits may not be widely accessible by default. This possibility has prompted calls for international AI benefit sharing: efforts to support and accelerate international access to AI's economic or broader societal benefits.

These and related calls have been made by a wide range of actors, from the UN's AI Advisory Body to frontier AI companies like OpenAI and Google DeepMind. Motivations for expanding access to AI technology and benefits range from supporting inclusive economic growth and development, to promoting technological self-determination, to advancing strategic geopolitical objectives. Individuals now associated with the Trump administration have emphasized the strategic importance of promoting access to American AI technology abroad to counter adversaries' influence in emerging markets.

In a new GovAI Report, we aim to bring clarity to these overlapping discussions. We cover:

• The diverse motivations driving calls for benefit sharing
• Concrete options for implementation
• Key challenges and obstacles
• Potential next steps for advancing benefit-sharing initiatives
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This post summarizes the report (see also figure 1); for more detail, you can read the full report here.

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Motivations for benefit sharing

We identify three distinct motivations behind calls for AI benefit sharing. 

First, some actors may support benefit sharing in order to accelerate inclusive economic growth and development. Advanced AI could significantly increase economic productivity while addressing challenges in healthcare, education, and agriculture. However, without proactive effort, these benefits might be slow to reach developing countries that can less readily access and deploy AI systems. The gains from AI may also be uneven within countries. Ultimately, benefit sharing may be able to help accelerate the spread of AI’s benefits to people they would otherwise be slow to reach.

Second, some advocate for benefit sharing to support technological self-determination. Currently, AI development is concentrated in a few high-income countries and China. This raises the possibility of technological dependency, with most nations reliant on foreign AI systems while having little influence over their development. Some advocates therefore approach benefit sharing as a means to help more countries develop indigenous AI capabilities and advocate for their interests in shaping the technology's trajectory.

Third, some analysts, especially in leading AI states, may see benefit sharing as a way to advance geopolitical goals. These geopolitical motivations include:

• Strengthening strategic partnerships and countering adversaries' influence in emerging markets. For instance, expanding access to US technology could help secure market share relative to China while building support for US-led approaches to AI development and governance 
• Incentivizing participation in international safety standards by making access to AI benefits conditional on adopting common governance frameworks
• Tempering risky competitive dynamics in AI development by reducing the perceived costs of “losing” an AI race
• Bolstering collective international security by sharing defensive AI applications, like those that enhance cybersecurity or detect emerging pandemics

This strategic dimension could prove particularly important as competition between the US and China intensifies.

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Options for implementation

Despite interest in benefit sharing, different stakeholders may envision different approaches based on their underlying motivations. We identify three broad categories of what could be shared, each of which raises strategic considerations (figure 2).

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These are:

• Sharing AI Development Resources: This approach involves distributing the fundamental inputs needed to develop and deploy AI systems, from computing power to technical expertise. This could include sharing compute through subsidized infrastructure or cloud services, supporting technical talent development through training programs, sharing valuable datasets, or sharing information about AI model training procedures. For example, governments or companies could create shared compute pools, similar to how multiple states pool resources for particle physics research at CERN, or could subsidize cloud compute access for developers in low-income countries.
• Sharing Access to Advanced AI Systems: This approach focuses on making existing AI systems and applications more widely accessible to users internationally. Leading AI companies and states could expand access to advanced AI systems through subsidies or differential pricing, for example. For instance, companies could implement region-based pricing to make their systems more affordable in lower-income countries, or frontier AI states could provide export financing to enable access to domestically developed AI technologies. R&D to reduce the costs of serving advanced AI systems could boost access and affordability as well. Access-sharing initiatives could focus particularly on applications that advance sustainable development goals.
• Sharing Financial Proceeds: This approach involves redistributing a portion of the economic gains generated by AI development internationally. This could happen through voluntary corporate initiatives, like companies committing to give away profits above certain thresholds, or through public mechanisms like increased international development funding fuelled by AI-driven economic growth. Other proposals include creating a multilateral global fund or a version of an “AI Growth Bond” that would acquire shares in AI companies and distribute dividends internationally.

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Various actors will see different advantages and challenges in each approach according to their motive for pursuing benefit sharing. Resource sharing could enable more countries to develop their own AI capabilities (a key goal for actors with “self-determination” motives) but raises security concerns associated with the proliferation of powerful dual-use technologies. Redistributing key resources needed for AI development could also slow progress at the frontier, delaying benefits from accelerated science and technological progress (and potentially jeopardizing the geopolitical goals of leading states). Access sharing might be relatively tractable, but requires careful governance to prevent malicious use. Financial proceeds sharing offers the most flexibility for recipients but faces significant implementation hurdles, and may not address concerns around self-determination and participation in AI development. 

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A comprehensive benefit-sharing framework would likely need to combine elements from multiple approaches, with different actors leading different initiatives.

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Challenges and Downsides

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Moving from proposed benefit-sharing initiatives to implementation will likely face several significant obstacles. In the report, we identify five challenges relevant to each of the benefit-sharing approaches discussed above:

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• Benefit sharing may prove redundant if AI benefits diffuse widely through market forces alone. Many AI capabilities are already spreading globally – for instance, open source models have been downloaded hundreds of millions of times across over 150 countries, while API costs for advanced models are falling rapidly. Economic incentives alone may widen access as companies seek to attract new users and reach new markets.
• Implementation could be intractable given  key actors’ incentives and constraints. Companies may resist sharing valuable resources or profits, while states may be reluctant to divert resources or share strategically important AI models.
• Expanding access to advanced AI systems and development resources could increase certain risks if it leads future high-risk capabilities to diffuse. Potential risks range from enabling misuse (like surveillance or bioweapons development) to intensifying competitive pressures that make AI development less safe. This effect may be mitigated to some extent by responsible governance mechanisms.
• Geopolitical considerations may may limit forms of benefit sharing that are primarily motivated by inclusive growth or self-determination goals. Leading states increasingly see AI capabilities as strategic assets, implementing export controls and other restrictions to secure access to AI resources and technologies. This could constrain efforts aimed at promoting technological self-determination or inclusive economic growth. US–China competition, in particular, could give  states reasons to be particularly selective about what they're willing to share and with whom.
• For states pursuing self-determination, a significant challenge is that some benefit sharing arrangements could create dependencies that frontier AI states may use to influence recipient countries.. Of course, frontier states pursuing geopolitical objectives may instead consider this effect of benefit sharing to be a positive feature.
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These challenges highlight the need for careful program design that considers safety, security, and international power dynamics. Some forms of benefit sharing – like expanding access to defensive AI applications – likely come with fewer downside risks than others.

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Conclusion and Next Steps

While these challenges require careful consideration, the rapid advancement of AI capabilities means discussions about benefit sharing are timely. Understanding how different approaches align with different objectives, and what trade-offs they involve, will become increasingly relevant as AI systems grow more strategically and economically important.

The range of motivations and options mean that benefit sharing might emerge through multiple channels simultaneously, with broad international dialogues occurring in fora like the UN's planned “Global Dialogue on AI Governance” occurring alongside bilateral partnerships and trade agreements that advance specific strategic interests.

These discussions also connect to broader questions about AI governance. As AI capabilities advance amid growing international competition, benefit sharing could influence both how AI's benefits are distributed and how states cooperate on governance challenges These decisions made about benefit sharing in the coming years may have lasting implications for global economic development – and the trajectory of AI progress

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