Artificial Intelligence and Global Affairs

Introduction

Artificial intelligence (AI) refers to computer systems designed to perform tasks that commonly require human cognitive abilities, such as learning, reasoning, prediction, language processing, perception, and decision support. Advances in machine learning, generative AI, robotics, and autonomous systems are transforming economies, governments, security institutions, and international relations.

AI has become a matter of global affairs because its development and use affect national power, economic competitiveness, military capabilities, information security, human rights, and the distribution of technological benefits. Countries compete to develop advanced AI systems while also exploring ways to manage shared risks through international cooperation.

1. Core Concepts in Artificial Intelligence

1.1 Machine Learning

Machine learning is a branch of AI in which systems learn patterns from data to make predictions, classifications, or decisions. It is used in translation, fraud detection, medical analysis, logistics, and many other fields.

1.2 Deep Learning

Deep learning uses multilayered artificial neural networks to process complex data, including images, audio, and text. It has contributed to major advances in speech recognition, computer vision, and generative AI.

1.3 Generative AI

Generative AI produces new content, including text, images, audio, video, and computer code, based on patterns learned from training data. It can support education, research, public administration, and productivity, but can also produce false or misleading content.

1.4 Large Language Models

Large language models are AI systems trained on large amounts of text and related data to generate or process language. Their outputs can be useful but may contain factual errors, fabricated references, or biased assumptions.

1.5 Artificial General Intelligence

Artificial general intelligence (AGI) is a hypothetical or aspirational category referring to AI with broad capabilities across many intellectual tasks, rather than systems restricted to particular functions. There is no universally agreed operational definition of AGI, and claims about its achievement should be evaluated carefully.

1.6 AI Agents and Autonomous Systems

AI agents can pursue defined objectives by interpreting information, planning steps, and taking actions through connected tools or systems. Their degree of autonomy varies. More autonomous systems raise questions about oversight, reliability, accountability, and human control.

2. AI as an Instrument of National Power

AI can influence national power through several channels.

2.1 Economic Competitiveness

AI can improve productivity, automate routine tasks, accelerate research, and create new industries. Countries with advanced computing infrastructure, skilled workers, reliable energy, capital, and access to data may gain economic advantages.

2.2 Military Capabilities

Military applications include intelligence analysis, surveillance, logistics, cyber defence, target recognition, simulation, and decision support. AI may accelerate military decision-making, but errors or overreliance on automated recommendations can create serious risks.

2.3 Intelligence and Strategic Assessment

AI can process satellite imagery, open-source information, communications data, and other large datasets. These capabilities may improve situational awareness while also creating concerns about privacy, surveillance, misinterpretation, and information manipulation.

2.4 Public Administration

Governments may use AI to improve service delivery, identify irregularities, translate documents, support planning, and analyse public data. These uses require safeguards against discrimination, unjustified surveillance, and opaque decisions.

2.5 Scientific and Technological Leadership

AI can accelerate scientific discovery in fields such as materials science, medicine, energy, and agriculture. Leadership depends not only on algorithms but also on computing capacity, research institutions, energy, data, talent, and industrial supply chains.

3. AI and Great-Power Competition

AI is increasingly connected to strategic competition among major powers, especially the United States and China, alongside efforts by the European Union and other countries to build their own capabilities.

Key areas of competition include:

• Advanced AI models and computing systems.
• Semiconductor design and manufacturing.
• High-performance computing and data centres.
• Access to skilled researchers and technical talent.
• Standards, regulation, and international governance.
• Military applications and intelligence capabilities.
• Export controls and protection of strategic technologies.

AI competition is not simply a contest to build the most powerful model. It also involves energy supply, manufacturing capacity, software ecosystems, research networks, access to markets, and the ability to deploy AI safely and effectively.

4. AI and International Security

4.1 AI-Enabled Warfare

AI may support faster surveillance, intelligence processing, logistics, and battlefield decision-making. Its military use raises concerns about escalation, miscalculation, civilian harm, and the reliability of automated systems in unpredictable conditions.

4.2 Autonomous Weapons

Autonomous weapon systems can select or engage targets with varying degrees of human involvement. International debates focus on meaningful human control, compliance with international humanitarian law, accountability, and limits on unacceptable uses.

4.3 Cybersecurity

AI can help defenders detect threats, identify unusual network activity, and respond to incidents. It can also assist malicious actors in creating convincing phishing messages, analysing vulnerabilities, or scaling certain forms of cyber abuse.

4.4 Disinformation and Information Operations

Generative AI can produce synthetic text, images, audio, and video at scale. Deepfakes and automated propaganda may be used to influence elections, damage reputations, incite violence, or undermine trust in institutions.

4.5 Strategic Stability

The use of AI in early-warning systems, intelligence assessment, and military command structures may affect crisis decision-making. If leaders rely on rapid but uncertain machine-generated assessments, the time available for human verification may shrink.

5. Economic and Social Implications

5.1 Labour Markets

AI can automate some tasks, augment others, and create new occupations. The effects depend on the nature of work, the pace of adoption, worker skills, labour institutions, and whether productivity gains are broadly shared.

5.2 Inequality

Countries and communities with limited computing infrastructure, capital, digital skills, or reliable electricity may struggle to benefit from AI. Unequal access could widen differences in income, productivity, and public services.

5.3 Education and Skills

AI can support tutoring, translation, research, and accessible learning materials. Educational systems must also address academic integrity, inaccurate outputs, privacy, and unequal access to technology.

5.4 Health and Scientific Research

AI may assist medical imaging, drug discovery, disease surveillance, and clinical administration. Its effectiveness depends on data quality, validation, clinical oversight, and appropriate protection of personal information.

5.5 Energy and Environmental Impacts

Large AI systems require computing infrastructure and electricity. Data centres can increase demand for power, cooling, water, and hardware. The environmental impact depends on energy sources, efficiency, infrastructure design, and the applications being used.

6. Global AI Governance

Global AI governance consists of international principles, institutions, standards, regulations, and cooperation aimed at encouraging beneficial uses of AI while managing risks.

6.1 United Nations and International Cooperation

The United Nations provides a forum for discussing AI’s implications for development, human rights, security, and international cooperation. The UN General Assembly established the Global Dialogue on AI Governance, whose inaugural session took place in Geneva on 6 and 7 July 2026. The initiative brings governments and stakeholders together to discuss common approaches and share experience. <Cite refs={[“turn733098search8″,”turn733098search11”]} />

6.2 UNESCO Recommendation on the Ethics of AI

UNESCO’s Recommendation on the Ethics of Artificial Intelligence, adopted in 2021, sets out principles relating to human rights, transparency, fairness, accountability, environmental considerations, and human oversight.

6.3 OECD AI Principles

The OECD AI Principles promote trustworthy AI, human-centred values, transparency, robustness, safety, and accountability. They influence policy discussions and international cooperation, although they are not a global treaty.

6.4 European Union AI Act

The EU AI Act establishes a risk-based legal framework for AI within the European Union. It distinguishes among different categories of AI uses and imposes requirements or restrictions according to their risks. Its reach may influence international businesses whose systems or services fall within its scope.

6.5 National AI Strategies

Many countries develop national AI strategies addressing research, skills, infrastructure, public services, industrial policy, and regulation. Differences among national approaches can create challenges for cross-border services and international standards.

7. Key Governance Challenges

• Safety and reliability: Systems may fail in unexpected circumstances.
• Transparency: Users may not understand how a system reaches a result.
• Bias and discrimination: Data and design choices can produce unfair outcomes.
• Privacy: AI can enable extensive collection and analysis of personal information.
• Accountability: Responsibility may be difficult to assign among developers, deployers, and users.
• Intellectual property: Training data and generated content raise legal and ethical questions.
• Concentration of power: Advanced computing and capital are concentrated in a limited number of companies and countries.
• Global inequality: Developing countries may lack resources to shape governance or build domestic capacity.
• Dual-use risks: Technologies developed for beneficial purposes may also be used for harmful ends.
• International coordination: National rules may differ in definitions, enforcement, and acceptable levels of risk.

8. AI and Developing Countries

Developing countries face both opportunities and constraints. AI may improve agricultural advice, health services, public administration, language access, education, and disaster response. However, benefits require reliable electricity, connectivity, affordable computing, relevant datasets, trained personnel, and effective institutions.

Countries should assess whether AI systems work in local languages and contexts. Imported systems may perform poorly when training data underrepresents local populations or conditions. Governments can build capacity through education, research partnerships, open and interoperable systems, regional cooperation, and proportionate regulation.

For Pakistan and similar countries, relevant policy issues include digital infrastructure, technical education, local-language AI, public-sector modernization, data protection, cybersecurity, and the development of domestic technological capabilities.

9. Key Distinctions

10. Related Glossaries

• Cybersecurity and Cyber Warfare
• Digital Governance and Digital Sovereignty
• Technology Competition and Semiconductor Geopolitics
• Autonomous Weapons and Future Warfare
• International Security
• Global Development and Inequality

Conclusion

Artificial intelligence is becoming a major instrument of economic competitiveness, public administration, scientific progress, and national security. Its strategic importance extends beyond software to computing infrastructure, semiconductors, energy, talent, data, and governance. The central international challenge is to enable innovation while protecting rights, reducing risks, and ensuring that the benefits are not confined to a small group of countries and companies.

36 Key Takeaways for Exams

1. AI refers to systems performing tasks associated with human cognitive abilities.
2. Machine learning enables systems to identify patterns in data.
3. Deep learning uses multilayered artificial neural networks.
4. Generative AI creates content such as text, images, audio, and code.
5. Large language models process and generate language.
6. AGI is a proposed category of broad, general-purpose AI.
7. AI agents can plan and take actions toward defined objectives.
8. AI can increase economic productivity and competitiveness.
9. AI leadership depends on computing, energy, data, talent, and capital.
10. The United States and China are important actors in AI competition.
11. Semiconductor supply chains are strategically important to AI.
12. AI can support intelligence analysis and military logistics.
13. Autonomous weapons raise questions of human control and accountability.
14. AI can strengthen cybersecurity and also enable malicious activity.
15. Deepfakes can undermine trust and distort public debate.
16. AI may affect the speed of crisis decision-making.
17. AI can automate some tasks and augment others.
18. Unequal AI access may widen international economic disparities.
19. AI can support education but raises integrity and reliability concerns.
20. Medical AI requires validation and appropriate oversight.
21. Data centres have energy, water, and environmental implications.
22. Global AI governance involves principles, institutions, and national laws.
23. The UN provides a forum for international AI cooperation.
24. The UN Global Dialogue on AI Governance held its inaugural session in July 2026.
25. UNESCO adopted its Recommendation on the Ethics of AI in 2021.
26. OECD AI Principles promote trustworthy and human-centred AI.
27. The EU AI Act uses a risk-based regulatory approach.
28. AI systems can reproduce or amplify bias.
29. Privacy is a central AI governance issue.
30. Accountability can be difficult when many actors contribute to a system.
31. AI technologies can have both beneficial and harmful uses.
32. Developing countries need infrastructure and skills to benefit from AI.
33. Local-language performance is important for inclusive AI.
34. National AI strategies address skills, infrastructure, and innovation.
35. International standards can reduce fragmentation but may reflect unequal influence.
36. Effective AI governance must balance innovation, safety, rights, and inclusion.