Proposals

International Cooperation Proposals

Given these challenges, a flexible, multi-tiered framework for international AI regulation is the global desideratum. This framework should operate through a combination of binding international agreements and voluntary, non-binding standards that can adapt to regional and sectoral differences. Drawing from previous research, we identify key components for such a framework: • Global AI Risk Taxonomy: A global AI risk taxonomy, akin to the one proposed in this survey, could provide a unified language for discussing AI risks across sectors and countries. This taxonomy would categorize risks into different levels, focusing on critical areas such as data privacy, bias, and misuse. By standardizing how risks are understood and communicated, international actors can more easily align on policy priorities. • International AI Standards: Building on existing initiatives, international standards could be developed under the auspices of a global body such as the United Nations or the World Trade Organization. These standards would focus on ensuring AI systems’ transparency, accountability, and fairness. A global AI council could be established to oversee compliance with these standards, with mechanisms for voluntary reporting and peer review (Zhang et al., 2022). • Data Governance and Privacy: One of the most critical areas for cooperation is data governance, given the central role of data in AI development. The General Data Protection Regulation (GDPR) in Europe provides a template for robust data protection, but international frameworks are needed to manage cross-border data flows and prevent abuses, particularly in countries with weaker regulatory environments (Barker, 2023). This could involve multilateral agreements on data-sharing protocols and privacy standards, facilitated by international organizations. • Ethics and Human Rights: AI governance must be grounded in universal ethical principles and human rights. This includes ensuring that AI technologies do not exacerbate existing inequalities or infringe on human rights. The UNESCO Recommendation on the Ethics of AI is a step in this direction, but further cooperation is required to ensure that these principles are embedded in national laws and international agreements (Meltzer & Kerry, 2021). • Technological Sovereignty and National Security: To address concerns about the geopolitical implications of AI, international treaties should balance technological sovereignty with security cooperation. This would ensure that AI technologies with potential military applications are subject to export controls and international oversight (Zhang et al., 2022). In conclusion, as AI technology continues to evolve, the need for international cooperation in its regulation becomes more urgent. National regulations, while necessary, are insufficient to manage the global risks posed by AI. An international framework that promotes cooperation, harmonizes standards, and balances innovation with safety is essential. Drawing on existing regulatory efforts and risk taxonomies, we propose a flexible, multi-tiered framework with identified key components to AI governance, one that can adapt to the diverse needs and priorities of different countries while ensuring the responsible development of AI.

Technical oversight proposals

Technical oversight in AI regulation involves a variety of components that ensure AI systems adhere to ethical and safety standards. These components include transparency and explainability, auditing and monitoring, accountability mechanisms, and the establishment of safety standards and certification processes.

Ethics and Compliance Proposals

The dual imperatives of ethical AI and regulatory compliance require robust frameworks that can adapt to the growing complexities of AI. This survey seeks to analyze current ethics and compliance proposals, with a focus on human-centered, responsible AI (HCR-AI), the need for sustainability, and the implementation of AI governance models.