据了解，作为联合实验室的牵头方，联合国统计大数据和数据科学全球中心由联合国经社部、国家统计局及浙江 省人民政府三方共建，旨在为全球数据治理与共享输出中国智慧。 联合国粮食及农业组织顾问 洛伦佐：中国在大数据领域已经形成了从基础研究到产业应用的完整链条，联合实验 室的组建，将通过整合科研机构的创新资源，把成熟实践经验服务于全球。 今天，由联合国统计大数据和数据科学全球中心牵头，联合之江实验室、浙江工商大学共建的数据科学联合实验 室正式揭牌。实验室将整合之江实验室等科研平台在大模型、人工智能领域的技术优势，围绕统计大数据和数据 科学领域的关键技术瓶颈，开展攻关研究。 联合国粮食及农业组织顾问 洛伦佐：中国在大数据领域已经形成了从基础研究到产业应用的完整链条，联合实验 室的组建，将通过整合科研机构的创新资源，把成熟实践经验服务于全球。 据了解，作为联合实验室的牵头方，联合国统计大数据和数据科学全球中心由联合国经社部、国家统计局及浙江 省人民政府三方共建，旨在为全球数据治理与共享输出中国智慧。 联合国统计大数据和数据科学全球中心管理处处长 刘小宁：把浙江的一些数字经济方面的研发成果，能够给国际 的专家学者提供一些中国 ...

Core Points - The Chinese Academy of Engineering has elected 24 foreign academicians for the year 2025 [1][2][3] Group 1: Elected Academicians - The list includes academicians from various countries and their respective research fields, such as mechanical manufacturing and automation from the UK, and marine engineering from Portugal [4][6][10] - Notable names include Shigeo Maruyama from Japan specializing in mechanical engineering and Carlos Guedes Soares from Portugal focusing on shipbuilding and ocean engineering [4][10] - The elected academicians represent a diverse range of disciplines, including data science, artificial intelligence, and biomedical engineering [6][19]

Group 1 - Hong Kong ranks fourth globally in the latest IMD World Digital Competitiveness Ranking 2025, improving three positions from the previous year [1] - In the three factors assessed, Hong Kong maintains strong performance in "Technology" and "Knowledge," ranking third and fifth respectively, while its ranking in "Readiness" has significantly improved by five positions to tenth [1] - Key sub-factors include "Technology Framework" and "Adaptive Attitude," both ranking first globally, with "Talent" and "Training and Education" also in the top five [1] Group 2 - The Hong Kong government is implementing measures to establish itself as an international innovation and technology hub, as announced in the 2025 Policy Address [2] - Initiatives include advancing the assembly of two pilot lines at the Hong Kong Microelectronics Research Institute and completing the establishment of the Life Sciences Research Institute and the Hong Kong Artificial Intelligence Research Institute within the next year [2] - The government is accelerating new industrialization by expediting the construction of the third "InnoHK Innovation Hong Kong R&D Platform" and lowering application thresholds for the "New Industrial Acceleration Program" [2] - A $3 billion AI funding plan is in place to meet local industry demand for computing power, with the Digital Port AI Supercomputing Center set to enhance its capabilities this year [2] - The government is also promoting AI business applications and will begin operations at the Hong Kong Park of the Lok Ma Chau Loop Technology Innovation Cooperation Zone this year [2]

Core Viewpoint - The need for high-quality data set construction in China is emphasized, with a call for scientists to adopt a public perspective and scientific vision to drive this initiative [1][4]. Group 1: High-Quality Data Sets - China possesses the capability and research strength to establish high-quality data sets, supported by both domestic and international observational data [1]. - Breakthroughs have been achieved in constructing high-quality marine data sets, with test results meeting or exceeding international standards [1][4]. - The construction of high-quality data sets requires leadership from relevant departments to organize scientists and ensure effective implementation [4]. Group 2: Statistical Analysis and Big Data - Traditional statistical methods face challenges in handling "ultra-high-dimensional" data, particularly in fields like genetics and geophysics, where data dimensions can reach millions while sample sizes remain small [1]. - There is a need for innovative hypothesis testing methods to address the complexities of high-dimensional data analysis [1]. - Statistical methods can serve as a common language across various fields, facilitating cross-domain applications of big data [2]. Group 3: Artificial Intelligence and Statistics - The integration of artificial intelligence (AI) and statistics is crucial, as AI models are fundamentally data-driven and share commonalities with statistical models [2]. - Simple statistical models should be prioritized before resorting to complex AI models, especially in scenarios with limited data [2]. - The importance of uncertainty measurement in AI and statistical methods is highlighted, as high uncertainty can render estimates meaningless [2]. Group 4: Talent Development - There is a significant talent gap in data analysis, including AI, necessitating enhanced training and educational programs [3]. - Tsinghua University is actively developing relevant undergraduate and master's programs to address this talent shortage [3].

Group 1 - The core viewpoint emphasizes that artificial intelligence (AI) will reshape the global labor market, affecting existing job structures and leading to a new technological revolution with unprecedented opportunities and challenges [2][4] - AI is transitioning from a "tool" to a "labor force," enhancing work efficiency and potentially replacing human jobs in various sectors, particularly in traditional industries [2][4] - The introduction of AI in manufacturing, finance, and healthcare is already demonstrating significant potential, with applications like automated production lines, algorithmic trading, and AI-assisted diagnostics [2][4] Group 2 - One of the major concerns regarding AI proliferation is the potential for "mass unemployment," particularly in sectors reliant on low-skill, repetitive jobs such as customer service and data entry [3][4] - The labor market will undergo a dramatic restructuring, where adaptability to new technologies will be crucial for both companies and individuals to benefit from the technological revolution [4][5] - Traditional industries such as manufacturing and transportation are expected to be the first to experience significant impacts from AI, with labor-intensive sectors facing substantial job reductions [4][5] Group 3 - In manufacturing, the rise of robotics and automated production lines will lead to the replacement of many manual and mechanical jobs, particularly in mid to low-end production roles [5] - The transportation sector will also be affected by AI, with the advent of autonomous driving technologies likely to reduce the demand for drivers significantly [5] - Despite the challenges faced by traditional industries, new job opportunities will emerge in fields such as data science, AI algorithm engineering, and smart hardware development [5][6] Group 4 - Governments and society must address how to protect workers' interests and promote skill upgrades in the face of accelerating AI adoption [6] - Policies encouraging retraining and career transitions for displaced workers are essential for helping them integrate into new industries [6] - A cautiously optimistic view suggests that AI's proliferation will not entirely destroy the job market but will instead create more innovation and opportunities, contingent on effective education and policy measures [6]