2025-02-09-世界经济论坛-智能经济蓝图——通过区域合作提高人工智能竞争力(英)_21页_899kb
报告摘要
AI Governance Alliance & KPMG White Paper: Blueprint for Intelligent Economies
Executive Summary
- AI presents transformative potential across economies and societies when developed responsibly and equitably.
- Requires global collaboration and cross-sector partnerships to prevent widening the digital divide.
- Provides strategic objectives for AI governance through three connected layers:
- Building sustainable AI infrastructure
- Curating diverse, high-quality datasets
- Establishing guardrails for ethics, safety and security
Key Strategic Objectives
Building Sustainable AI Infrastructure
- Challenges: Energy-intensive infrastructure, inconsistent supply chains, high costs
- Solutions:
- Renewable energy partnerships
- Efficient model development
- Diversified procurement networks
- Tax incentives & sovereign cloud initiatives
Curating Diverse, High-Quality Datasets
- Critical for equitable AI development representing global communities
- Strategies:
- Open data platforms
- Synthetic data programs
- Language preservation initiatives
- Regional data sovereignty frameworks
Establishing Guardrails for Responsible AI
- Ensures ethical AI deployment aligned with societal values
- Framework components:
- Human-centric design principles
- Regional compliance mechanisms
- IP standards development
- Bias mitigation approaches
Bridging the Digital Divide
- Recommendations for inclusive growth at multiple levels:
- Subsidized access to devices
- Technical workforce development
- Global standards coordination
- Regional infrastructure clusters
Stakeholder Collaboration
- Governments: Regulatory frameworks, strategic investment
- Enterprises: Responsible deployment, accessibility initiatives
- Academia: Research, education programs
- Civic Society: Advocacy networks, local implementation
Call to Action
- Requires multistakeholder engagement at local, national, and international levels.
- Provides foundation for strategic implementation pilots.
- Emphasizes integrated approach to sustainable AI development.
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