5月23日，中国国家互联网信息办公室副主任王京涛在京应约会见巴西公共管理与创新部常务副部长克 里斯蒂娜.莫里一行，双方围绕网络安全、人工智能治理等议题进行深入交流。(智通财经) ...

Group 1 - The core idea emphasizes the necessity of mutual learning between different civilizations in the context of artificial intelligence reshaping human civilization, highlighting the integration of Western rationalism and Eastern holistic thinking in AI governance [1][6] - Western rationalism provides a methodological foundation for AI governance, as seen in the EU's AI Act which incorporates principles of technological transparency into legal frameworks [1][3] - Eastern holistic perspectives inject ecological wisdom into technological development, as demonstrated by China's AI ethics guidelines that prioritize ecological considerations alongside economic benefits [2][4] Group 2 - The governance paradigm is evolving towards a collaborative model that balances rights protection and shared responsibilities, with the EU's GDPR establishing a robust rights protection network while China emphasizes ethical risk management in AI development [3][4] - The integration of rights and responsibilities is not contradictory but rather a dialectical unity that forms a new governance paradigm, providing a reference model for global AI governance [4][5] - A dynamic balance between technological innovation and humanistic care is essential, as evidenced by the contrasting approaches to data governance and algorithm management in the West and East [4][6] Group 3 - The mutual learning between civilizations is seen as a pathway to a shared future, with initiatives like UNESCO's AI ethics recommendations reflecting a synthesis of Eastern and Western philosophical wisdom [5][6] - The essence of AI governance is framed as a choice of values, where Western precision meets Eastern ecological wisdom, creating governance insights that transcend cultural boundaries [6]

当前，我国正处于开启全面建设社会主义现代化国家新征程、向第二个百年奋斗目标进军的重要历史节 点，人工智能是发展新质生产力、推动高质量发展、跨域式助力中国式现代化的新优势和新动能。从赋 能千行百业、优化社会治理到改善民生福祉、加速科研突破，人工智能的应用前景无限广阔。我国拥有 海量数据资源、完备产业体系、广阔应用场景和巨大市场空间，这为人工智能技术的迭代创新与深度应 用提供了得天独厚的优势。牢牢抓住这一优势，推动人工智能与实体经济深度融合，赋能传统产业转型 升级，催生新产业新业态新模式，将技术潜力转化为实实在在的发展效能。在拥抱人工智能发展机遇的 同时，绝不能忽视其带来的潜在风险与严峻挑战。算法偏见、数据滥用、隐私泄露、深度伪造、就业冲 击、伦理失范乃至技术失控等风险，不仅可能扰乱经济社会秩序，甚至可能对国家安全和国际秩序构成 威胁。特别是在当前复杂严峻的国际形势下，个别西方国家将科技问题政治化，大搞技术封锁和"小院 高墙"，企图利用人工智能遏制他国发展，加剧了全球人工智能领域的不确定性和安全风险。面对这把 锋利的"双刃剑"，既要勇于拥抱变革、抢抓机遇，也要始终保持清醒头脑，坚持底线思维，做到未雨绸 缪。 如何 ...

Core Viewpoint - Open science is emerging as a transformative paradigm in research, emphasizing the need for international cooperation and open sharing of scientific knowledge to address global challenges [1][2][3] Group 1: Importance of Open Science - Open science is essential for enhancing scientific collaboration and information sharing, allowing science to benefit society [1] - The necessity for open science is increasingly urgent due to global sustainability demands, such as climate change and biodiversity [1][2] - Open science represents a shift from traditional research paradigms, advocating for open access to research results and data [1] Group 2: Challenges and Solutions - The current era is characterized by complex, interconnected challenges that cannot be addressed by individual countries or laboratories alone [2] - To promote open science, it is crucial to improve policy environments, share experiences, and create frameworks that support open science initiatives [3] - Establishing a global scientific community is vital for addressing challenges like climate change and health crises, necessitating international collaboration on large-scale scientific projects [3] Group 3: Mechanisms for Open Science - Enhancing the sharing of research infrastructure and establishing international open sharing platforms can improve efficiency and resource utilization [3] - Open sharing is viewed as a potential accelerator for increasing research efficiency, speeding up technology diffusion, and fostering cross-national collaboration [2]