Program Outcome Report Sample

3rd Brief: ARTIFICIAL INTELLIGENCE

Catalyst for Cooperation or Conflict?

By Emerole Clinton Chimezie

Artificial intelligence will reshape power, wealth and human capability more profoundly than any other technological innovation since the industrial revolution. The question facing governments is not whether AI transforms the world—it already has—but whether that transformation occurs through cooperative frameworks or dangerous cutthroat competition.

Current trajectories point toward the latter. An AI arms race has already accelerated between major powers and access to AI infrastructure is being concentrated among a few nations and corporations. Frameworks lag years behind technological capabilities and without a deliberate intervention, AI risks becoming a catalyst for geopolitical conflict, economic inequality and societal disruption.

The alternative—AI as tool for humans to flourish, governed by shared standards and equitably accessible—requires urgent multilateral action. The window for establishing cooperative frameworks is still narrow and closely competitive.

The Strategic Landscape

AI's dual-use nature—applicable to both civilian innovation and military power—creates security dilemmas. Advances in machine learning enhance medical diagnostics and autonomous weapons simultaneously. Natural AI language improves education and enables sophisticated disinformation. Computer vision aids agricultural efficiency and mass surveillance.

This dual-use quality means the development of AI cannot be separated from geopolitical tensions.

When the U.S. restricts Chinese access to advanced semiconductors, when China invests over $150 billion in AI R&D, when the EU proposes comprehensive AI regulation—these are not merely economic or technological decisions. They are moves in a strategic competition for 21st-century dominance.

Three dynamics drive this escalation:

The Compute Divide: The capability of AI increasingly depends on access to massive computing power. Training cutting-edge models requires thousands of specialised chips and enormous energy. Only a handful of nations and companies possess this infrastructure. The U.S., China, and to a lesser extent the EU dominate and this unequal concentration creates dependencies and vulnerabilities.

The Data Advantage: AI systems learn from data. Nations with large populations, digital ecosystems and data collection capabilities possess structural advantages. China's surveillance state generates training data. American tech platforms harvest global behavioral data. Nations lacking digital infrastructure or privacy protections cede to this advantage entirely.

The Talent War: AI development requires specialised expertise. Global talent are mostly concentrated in Silicon Valley, Beijing, London, and a few other hubs. Nations compete aggressively for skilled AI researchers, offering visas, funding and research freedom. This zero-sum competition for finite talent accelerates as AI's strategic importance becomes clear.

Military AI: The Question of Autonomous Weapons 

Perhaps no AI application raises more intense stakes than autonomous weapons. Current AI systems enable drones that select and engage targets without human intervention, cyber weapons that adapt to defenses in real-time and information warfare tools that spread disinformation at machine speed.

Major powers invest heavily despite ethical concerns. The logic is grimly rational: if adversaries develop autonomous weapons, failing to compete leads to a strategic disadvantage on their part. This fuels a classic arms race —with each side racing to deploy capabilities they privately fear and unable to slow unilaterally.

The consequences could be catastrophic. 

Autonomous weapons lower barriers to conflict (no risk to soldiers), speed up warfare beyond human decision-making (flash wars decided in minutes) and raise accident risks (AI systems misinterpreting situations and escalating unintentionally).

Yet no binding international agreement restricts the development of autonomous weapons. The UN's Convention on Certain Conventional Weapons discusses but doesn't decide. Without an agreement, the race continues.

Economic AI: Inequality and Displacement

AI's economic impacts are distributed unevenly. Nations with AI-driven industries capture value while those providing only data or labor see limited benefits. 

Within nations, skilled AI workers thrive while routine cognitive workers face displacement.

The IMF projects that AI could affect at least 40% of the global workforce, with higher-skilled workers benefiting and lower-skilled facing replacement. This further exacerbates the inequality unless governments intervene with retraining safety nets and policies ensuring broad distribution of benefits.

Developing nations also face particular challenges. Without AI infrastructure, talent or capital, they risk becoming permanent data suppliers and algorithm consumers—a digital colonialism extracting value while providing little domestic benefit.

Disinformation and Social Fragmentation

Generative AI enables creation of convincing fake images, videos and human audio at a large scale. Disinformation campaigns that once required human labor now generate infinite content at a near-zero marginal cost.

The implications for democracy, journalism and social trust are profound. When citizens cannot distinguish real from synthetic, the main evidence loses it's meaning. Political manipulation becomes easier and more sophisticated. Authoritarian regimes deploy AI-enabled surveillance and propaganda. Democratic discourse gets more fragmented under floods of AI-generated falsehoods.

Existing content moderation struggles with human-generated misinformation and AI-generated disinformation at a large scale may overwhelm these systems entirely.

Paths to Cooperation

Yet cooperation remains possible—even rational. 

AI risks are genuinely global. No nation benefits from autonomous weapon accidents, uncontrolled AI development or collapse of already existing information. These shared risks create incentives for coordination like;

Global AI Safety Framework: Establish multilateral agreements on AI development standards by focusing initially on areas of clear mutual interest:

•Restrictions of Autonomous Weapons(modeled on chemical/biological weapons bans)

•Transparency requirements for high-stakes AI systems (healthcare, criminal justice, financial services)

•Mandatory impact assessments before deploying AI in critical infrastructure

•Incident reporting mechanisms for AI accidents or near-misses

Compute Sharing for Development: Advanced economies could provide subsidised access to AI computing infrastructure for researchers in developing nations. This reduces the unequal concentration, enables global AI talent participation and builds goodwill.

AI Ethics Standards: While a perfect consensus is totally impossible, minimum standards can emerge—prohibitions on explicitly harmful applications (social credit scores for political control, mass surveillance without oversight), requirements for human oversight in life-or-death situations and basic transparency about use of AI in public services.

Inclusive AI Governance: Current AI regulation discussions occur primarily among the U.S., EU, and Chinese policymakers. Expanding the participation to include Global South voices, civil society and independent researchers prevents governance capture by vested interests.

WGS as a Convening Platform

The World Governments Summit is ideally positioned to facilitate the AI cooperation. Unlike UN bodies (too slow and consensus-bound) or private sector forums (conflicts of interest), WGS can convene government leaders with authority to make binding commitments.

WGS should also establish an annual AI Governance Summit that'll be focused on;

1.Track-two diplomacy for U.S.-China AI de-escalation

2.Technical standards development with input from governments, researchers and key industry stakeholders 

3.Global AI Ethics Commission publishing recommendations on contentious questions

4.Developing nation capacity building for AI governance and participation

Policy Recommendations

Immediate (2026-2027):

•Convene major powers for preliminary AI safety discussions

•Commission Global AI Governance Index that'll be used for tracking national regulatory approaches. 

•Establish WGS AI Ethics Commission with diverse global representation

Medium-term (2028-2030):

•Negotiate multilateral agreements restrictions to autonomous weapons.

•Launch compute-sharing initiative for developing nations.

•Create AI incident reporting system for near-misses and failures

Long-term (2031-2040):

•Achieve binding international framework on AI safety comparable to nuclear non-proliferation

•To ensure that 150+ nations participate meaningfully in AI governance

•Demonstrate AI's potentials for cooperation through joint projects (disease detection, climate modeling, education)

Conclusion

AI is simultaneously humanity's greatest opportunity and its most dangerous creation too. It will cure diseases and enable personalised warfare. It will democratise education and automate employment. It will solve climate change and accelerate inequality.

Which outcomes prevail depends on choices governments make now—in the narrow window before AI capabilities outpace governance entirely.

Competition has momentum. Arms races, once started, are hard to stop. Economic advantages, once concentrated, are difficult to redistribute. Societal trust, once shattered by disinformation, is nearly impossible to rebuild.

But cooperation remains possible. Shared risks create shared interests. Technical solutions exist for governance challenges. Political will can be mobilised if leaders understand this stakes clearly.

The World Governments Summit can catalyse that understanding—and the action it demands. The choice between cooperation and conflict is not predetermined. It is ours to make.

The future is not yet written. But it is being coded—now and Governments must decide whether that code will be written collaboratively or competitively.