| 223 | 0 | 49 |
| 下载次数 | 被引频次 | 阅读次数 |
人工智能技术自诞生以来一直以前所未有的速度加速迭代,以DeepSeek为代表的大模型应用技术发展更是引领了新一轮科技革命和产业变革。在国内,我国高度重视人工智能技术的发展潜力和风险,正在逐步形成央地协同的人工智能法律监管体系。在国外,全球合作机制也在大国主导下正在形成。然而,人工智能技术,特别是以AI大模型为代表的衍生技术的发展在未来依然面临着数据、算力、立法等多种因素的不确定性,立法监管呈现“难产”的滞后性问题,国际合作也因世界各国价值观、政治利益的差异遭遇推进受阻。为此,深入剖析全球人工智能技术的发展趋势,分析发展所面临的挑战,结合我国发展实际提出应对举措。
Abstract:Since its inception, Artificial Intelligence(AI) technology has been evolving at an unprecedented pace. The development of Large Model Application Technology represented by DeepSeek has led a new round of technological revolution and industrial transformation. In China, the government attaches great importance to the development potential and risks of AI technology and is gradually forming a coordinated AI legal supervision system at the central and local levels. Abroad, a global cooperation mechanism is also taking shape under the leadership of major countries. However, the development of AI technology, especially derivative technologies represented by large AI models, still faces uncertainties in the future due to various factors such as data, computing power, and legislation. Legislative supervision shows a lagging problem of being “difficult to produce”, and international cooperation has also encountered obstacles due to differences in values and political interests among countries. Therefore, this article aims to deeply analyze the development trends of global AI technology and the challenges faced in its development, and propose countermeasures based on China's development.
[1] 董雅雯,李恒,刘佳,等.大模型技术的发展与应用:现状、机遇与挑战[J].人工智能,2025(1):110-118.
[2] 吴永兴,菅志宇,苏昌,等.生成式人工智能大模型的安全风险及治理路径[J].中国现代教育装备,2025(9):24-26.
[3] 耕虚财经.浅析人工智能算法解释权的构建[EB/OL].(2022-08-23)[2025-05-30].https://baijiahao.baidu.com/s?id=1741959386058546079&wfr=spider&for=pc.
[4] 司伟攀,刘鑫怡.美国算法治理分析及思考[J].全球科技经济瞭望,2022(11):34-40.
[5] 孔勇,李美桃,王伟,等.美国《人工智能风险管理框架》解读[J].中国信息化,2023(3):39-44.
[6] 梅阳,曾靖,湛泳.美欧人工智能监管合作、分歧及中国战略突围的“机会窗口”[J].中国科学院院刊,2025(4):715-724.
[7] 吴洁.中美欧人工智能监管治理比较[J].中国经济报告,2024(3):107-114.
[8] 张瑜.论我国人工智能立法的现实进路:基于欧盟《人工智能法》的风险分级监管模式[J].中国信息界,2025(1):105-107.
[9] 中央网络安全和信息化委员会办公室.政策法规[EB/OL].(2017-05-02)[2025-05-31].https://www.cac.gov.cn/wxzw/zcfg/bmgz/A09370303index_1.htm.
[10] 国务院办公厅.国务院2024年度立法工作计划[EB/OL].(2024-03-18)[2025-05-06].https://www.gov.cn/zhengce/content/202405/content_6950093.htm.
[11] 魏钰明,贾开,曾润喜,等.DeepSeek突破效应下的人工智能创新发展与治理变革[J].电子政务,2025(3):2-39.
[12] 朱力宇,胡晓凡.联合国教科文组织《人工智能伦理问题建议书》的借鉴启示及其中国贡献:以人权保障为视角[J].人权研究,2022(4):47-64.
[13] 王涛,宋海波,王青,等.WHO《卫生健康领域人工智能伦理与治理》指南简述与启示[J].中国药物警戒,2024(8):906-909.
[14] 钟新龙,彭璐.美欧人工智能法案对比研究及启示建议[J].科技中国,2023(6):32-35.
[15] 中国政府网.国务院关于印发新一代人工智能发展规划的通知[EB/OL].(2017-07-05)[2025-05-31].https://www.gov.cn/gongbao/content/2017/content_5216427.htm.
[16] 中国政府网.关于印发《科技伦理审查办法(试行)》的通知[EB/OL].(2023-09-07)[2025-05-31].https://www.gov.cn/gongbao/2023/issue_10826/202311/content_6915814.html.
[17] 张晓,陈晶晶,蒋熙韬.全球数字契约:大变局时代的一次集体行动[J].中国信息安全,2024(10):83-86.
[18] 安全内参.经合组织发布人工智能原则评析[EB/OL].(2019-06-05)[2025-05-31].https://www.secrss.com/articles/11178.
[19] 中央网络安全和信息化委员会办公室.全球人工智能治理倡议[EB/OL].(2023-10-18)[2025-05-31].https://www.cac.gov.cn/2023-10/18/c_1699291032884978.htm.
[20] WANG W G,YANG Y,WU F.Towards data-and knowledge-driven AI:a survey on neuro-symbolic computing[J].IEEE transactions on pattern analysis and machine intelligence,2025,47(2):878-899.
[21] SUN CN,HUANG S J,POMPILI D.LLM-based multi-agent decision-making:challenges and future directions[J].IEEE robotics and automation letters,2025,10(6):5681-5688.
[22] 程琳,张宏杰.人工智能时代网络意识形态建设的机遇、挑战与路径[J].邢台学院学报,2024(4):71-78.
[23] YANG Y J,ZHOU T Y,LI K X,et al.Embodied multi-modal agent trained by an LLM from a parallel TextWorld[C].2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),2024:26265-26275.
[24] HAYET I,SCOTT A,D’AMORIM M.ChatAssert:LLM-based test oracle generation with external tools assistance[J].IEEE transactions on software engineering,2025,51(1):305-319.
[25] 吴文峻,廖星创,赵金琨.DeepSeek技术创新与通用人工智能发展趋势[J].科技导报,2025(6):14-20.
[26] FAKHOURY S,NAIK A,SAKKAS G,et al.LLM-based test-driven interactive code generation:user study and empirical evaluation[J].IEEE transactions on software engineering,2024,50(9):2254-2268.
[27] 亚马逊云科技.湖仓一体是什么?[EB/OL].(2025-03-17)[2025-03-18].https://m.cyzone.cn/article/727707.html.
[28] 卢迪,李宽,任紫涵.人工智能全球生态视角下的智能体发展新态势[J].对外传播,2025(3):63-67.
[29] 林雨佳.生成式人工智能对信息治理的挑战与应对[J].苏州大学学报(哲学社会科学版),2025(2):104-115.
基本信息:
中图分类号:TP18;D912.1
引用信息:
[1]邓辉,张文娟,艾政阳.全球人工智能发展形势研判及对策建议[J].邢台学院学报,2025,40(06):83-93.
基金信息:
国家社科基金重大项目:网络信息安全监管的法治体系构建研究(2021&ZD194)