瞭望 | 人工智能治理：刀锋之舞

Core Insights - Artificial intelligence (AI) is a strategic technology driving the current technological revolution and industrial transformation, showcasing significant potential to alter production and lifestyle, as well as reshape the global economic landscape [2] - The AI industry in China is rapidly developing, with the core industry scale approaching 600 billion yuan by 2024, indicating a robust ecosystem encompassing foundational hardware and software, key technology research, and industry applications [2] - AI presents a dual-edged sword effect, driving economic growth while also introducing complex, unpredictable risks due to its unique characteristics, including systemic integration, cross-domain diffusion, value sensitivity, and dynamic adaptability [2][3] Industry Characteristics - The systemic nature of AI means it is deeply embedded in complex socio-economic networks, leading to widespread impacts [2] - AI technologies can quickly spread defects or ethical issues across different domains, potentially causing chain reactions [2] - The reliance on data and algorithms in AI decision-making can lead to hidden biases and ethical violations in critical areas [2] - Continuous learning and evolution of AI models can result in unpredictable risk developments beyond initial expectations [2] Governance Challenges - Traditional governance approaches may fail in managing AI due to its dynamic decision-making capabilities, necessitating a balance between risk control and innovation facilitation [4] - The complexity of AI governance involves reconciling multiple, often conflicting objectives, such as ensuring safety while promoting technological advancement [4] - The World Economic Forum's 2024 Global Risks Report identifies AI-generated misinformation as a top global risk, highlighting concerns over its potential to exacerbate global tensions [4] Global Governance Approaches - The governance of AI has become a strategic battleground among major powers, with the U.S., EU, and China adopting distinct governance models [5][6] - The U.S. favors a "light regulation" approach, emphasizing innovation and market-driven solutions while maintaining a focus on high-risk scenarios [5] - The EU adopts a "strong regulation" model centered on protecting individual rights and establishing clear compliance obligations, aiming to set a global benchmark for AI governance [6] - China is developing a comprehensive governance framework that includes ethical guidelines and regulatory measures across the AI lifecycle, emphasizing a balance between safety and development [7] Future Considerations - The effectiveness of different governance models will depend on various factors, including technological breakthroughs, application efficacy, and the evolving industrial ecosystem [8] - The ultimate goal of AI governance should be to serve humanity's long-term interests, ensuring dignity, fairness, safety, and control over one's destiny while leveraging AI's potential for societal progress [8][9]