Key Takeaways

• Top story: China calls for the creation of a global AI cooperation body at APEC, highlighting a widening rift as the US remains absent from talks.
• AI compliance is expected to shift from a regulatory burden to a source of competitive advantage by 2026, marking a turning point for global firms.
• South Korea introduces an ambitious AI-driven strategy to address demographic challenges, blending technology with societal adaptation.
• Deepfakes are forecasted to cause a major security breach next year, raising urgent questions about authenticity and digital trust.
• The ongoing redefinition of intelligence and governance shows how AI is reshaping not only policy but also the societal framework.
• The full context, deeper questions, and key reactions are detailed below.

Introduction

On 1 November 2025, China’s call for the creation of a global AI cooperation body at APEC highlights fresh tensions in AI governance and society. AI compliance is evolving from a regulatory obstacle to a competitive tool. Meanwhile, nations like South Korea are unveiling AI-driven strategies to address complex demographic challenges.

Top Story: China proposes new AI cooperation body at APEC

China announced a proposal for a new international AI governance body during the Asia-Pacific Economic Cooperation summit. The initiative, introduced by President Li during the opening plenary, seeks a multilateral framework focused on shared development and responsible innovation. This approach emphasizes establishing common standards while respecting national AI sovereignty.

This proposal arises against the backdrop of tensions over AI regulatory approaches. China is positioning itself as a connector of regional perspectives. President Li stated that technological development should not be another arena for division and called for cooperation that transcends ideological differences.

US participation remains uncertain. Vice President Harris is leading the American delegation in President Turner’s absence. This is the first time in eight years an American president has missed the summit, prompting questions about US commitment to Asia-Pacific AI coordination efforts.

Geopolitical implications

The proposal is seen as China’s most ambitious effort to shape global AI governance, potentially challenging Western-led models. Analysts such as Dr. Elena Korosteleva, an international relations professor at Oxford University, have stated that China is strategically filling a governance vacuum. By proposing inclusive frameworks while the US focuses inward, Beijing gains diplomatic capital with developing nations seeking technology access.

Regional responses are mixed. Indonesia, Thailand, and Malaysia have expressed preliminary support. Japan and Australia have adopted a more cautious stance, and both have emphasized the need for democratic values in AI governance structures.

Also Today: AI regulation and compliance

EU implements first phase of AI Act enforcement

The European Union began enforcement of the initial provisions of its landmark AI Act, requiring transparency disclosures for generative AI systems operating in the bloc. Companies must now label AI-generated content and document training data sources.

Compliance results are mixed. Major firms such as OpenAI and Anthropic have met requirements, while several smaller European companies have requested extensions. EU Digital Commissioner Breton stated that the grace period for adaptation is deliberately short. Enforcement actions will commence by mid-November.

The phased roll-out precedes the Act’s full enforcement in May 2026, providing businesses time to adapt to stricter requirements for high-risk AI systems. Industry groups have expressed concern that the phased approach creates regulatory uncertainty.

EU AI Act’s regulatory framework and compliance requirements have become pivotal in shaping international business strategies as nations respond to these new legal landscapes.

Canada finalizes AI guardrails legislation

The Canadian parliament approved the Artificial Intelligence and Data Act after months of debate, establishing what Prime Minister Trudeau called a principles-based framework balancing innovation and safety. The legislation introduces a risk-tiered system with disclosures required for high-impact AI systems.

Unlike the EU approach, Canada’s model emphasizes industry self-regulation and reporting, with government oversight activated only by significant harm or complaints. Civil liberties organizations have criticized this approach as insufficiently protective of citizen rights.

The bill introduces substantial penalties for non-compliance, with fines up to 6% of global annual revenue for serious violations. Implementation will begin in January 2026, overseen by a newly established AI Safety Office.

Also Today: AI and society

UNESCO report warns of widening AI divide

A new UNESCO study documents increasing disparities in AI capabilities between high-income and developing nations. The report, “Artificial Intelligence: Bridging Digital Divides,” finds that 76% of AI research publications and 89% of AI patents originate from only seven countries.

These disparities extend to implementation. Developing nations face significant barriers to integrating AI in public services. Without intervention, AI threatens to exacerbate rather than reduce social and economic inequalities. UNESCO Director-General Azoulay emphasized this point during the report launch.

The study recommends international knowledge transfer programs, targeted funding for developing nations, and capacity-building initiatives. In response, foundations including the Gates Foundation announced $450 million in new funding for AI education across 24 lower-income countries.

AI capabilities and access are also playing a role in conservation and biodiversity, reflecting how digital inequalities could have real-world environmental implications.

Research collaboration identifies algorithmic bias indicators

An international research consortium published a new framework for detecting and measuring algorithmic bias, as detailed in Science. This collaboration, involving researchers from 19 universities, established standardized metrics to assess fairness across AI applications and cultural contexts.

The framework identifies eight distinct forms of algorithmic bias. Notably, it highlights cultural context sensitivity, where AI systems perform inconsistently across regions or cultures. According to lead researcher Dr. Nandita Sharma of MIT, the team has created a universal metric for fairness.

Technology companies such as Microsoft and Google have committed to adopt these metrics in their development processes. Civil rights organizations have praised the work as a crucial step toward accountable AI and continue to call for regulatory requirements mandating bias testing.

Algorithmic fairness is being incorporated into HR and hiring technologies, with transparency models designed to reduce discrimination, as shown in ensuring fairness in AI hiring.

What to Watch: Key Dates and Events

• The APEC AI Governance Working Group meets from 3 to 5 November 2025 in Bangkok to formulate responses to China’s proposal.
• South Korea will unveil its comprehensive AI policy framework on 7 November 2025, including regulatory and research initiatives.
• The International Standards Organization (ISO) will host a regulatory roundtable on 12 November 2025 in Geneva to discuss global AI technical standards.
• The UN Secretary-General’s AI Advisory Body presents preliminary recommendations on 15 November 2025 at the United Nations headquarters.

Conclusion

China’s initiative to shape global AI governance emphasizes the need for collaboration amid a fragmented regulatory landscape. This move signals rising stakes for international influence over AI’s social impact. As regions deliberate over values and standards, the interaction between AI governance and society remains a contested domain. Coming up: regional policy meetings in November 2025 will reveal the momentum behind cooperative frameworks and define subsequent steps for multilateral AI oversight.

For a deeper dive into the ontological and philosophical roots of intelligence, see AI origin philosophy and how intelligence may be emerging through language and governance.