暨南学报(哲学社会科学版)

作者：谭新雨

单位：华东理工大学社会与公共管理学院。

关键词：生成式人工智能大模型,社会治理,互构理论,风险样态,AI治理

基金：华东理工大学研究生教育教学改革项目“教育、科技、人才一体融合视角下高校拔尖创新人才贯通培养模式研究”;上海市“科技创新行动计划”软科学青年项目“通用人工智能助力上海国际科创中心建设的机理与策略研究”(24692104200);高等教育科学研究规划课题重点项目“数智时代创新创业教育与服务区域发展研究”(22CX0306)。

中国式现代化进程中,生成式人工智能大模型(AI大模型)持续深入地嵌入社会治理体系中,推动了政府组织嬗变与治理模式革新,但也难免衍生出一些问题。本研究基于技术—社会、技术—组织互构理论对AI大模型嵌入社会治理的赋能场景、风险样态、规制路径展开分析。其中,AI大模型嵌入社会治理后使官僚决策从情感决策转向理性决策; 部门关系从碎片分割转向协同联动; 服务提供从刚性分配转向需求计算;治理模式从人工治理转向智慧治理。但与此同时,AI大模型治理模式也带来了道德/责任判定障碍,威胁公共伦理责任;带来了科学技术异化风险,威胁人类主体地位;带来了社会刻板偏见风险,威胁公平正义理念;带来了公民权利受损风险,威胁民主自由价值。由此,未来AI大模型治理体系应融入科技向善导向、 人本主义理念、公共价值目标、协同治理模式等。"/>template{display:none;}.mag-rich-xref-fn { cursor: pointer;}//长视频$(document).ready(function(){if($("#showLongArticleVideo") && $("#showLongArticleVideo").length && $("#showLongArticleVideo").length>0){mag_ajax_update({ele_id:'showLongArticleVideo',url:mag_currentQikanUrl() + "/CN/article/showLongArticleVideo.do?id="+$("#articleId").val()});}});$(document).ready(function(){window.metaData = {"journal":{"issn":"1000-5072","qiKanMingCheng_CN":"暨南学报（哲学社会科学版）","id":2,"qiKanMingCheng_EN":"Jinan Journal"},"fundList_cn":["华东理工大学研究生教育教学改革项目“教育、科技、人才一体融合视角下高校拔尖创新人才贯通培养模式研究”;上海市“科技创新行动计划”软科学青年项目“通用人工智能助力上海国际科创中心建设的机理与策略研究”(24692104200);高等教育科学研究规划课题重点项目“数智时代创新创业教育与服务区域发展研究”(22CX0306)。"],"article":{"keywordList_cn":["生成式人工智能大模型","社会治理","互构理论","风险样态","AI治理"],"juan":"46","zhaiyao_cn":"中国式现代化进程中,生成式人工智能大模型(AI大模型)持续深入地嵌入社会治理体系中,推动了政府组织嬗变与治理模式革新,但也难免衍生出一些问题。本研究基于技术—社会、技术—组织互构理论对AI大模型嵌入社会治理的赋能场景、风险样态、规制路径展开分析。其中,AI大模型嵌入社会治理后使官僚决策从情感决策转向理性决策; 部门关系从碎片分割转向协同联动; 服务提供从刚性分配转向需求计算;治理模式从人工治理转向智慧治理。但与此同时,AI大模型治理模式也带来了道德/责任判定障碍,威胁公共伦理责任;带来了科学技术异化风险,威胁人类主体地位;带来了社会刻板偏见风险,威胁公平正义理念;带来了公民权利受损风险,威胁民主自由价值。由此,未来AI大模型治理体系应融入科技向善导向、 人本主义理念、公共价值目标、协同治理模式等。","endNoteUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/article/getTxtFile.do?fileType=EndNote&id=7134","reference":"","bibtexUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=BibTeX&id=7134","articleType":"","abstractUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/10.11778/j.jnxb.20242259","qi":"12","id":7134,"nian":2024,"bianHao":"1736415776330-349407550","zuoZheEn_L":"TAN Xinyu","juanUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/Y2024","shouCiFaBuRiQi":"2025-01-09","qiShiYe":"97","qiUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/Y2024/V46/I12","lanMu_cn":"公共管理·人工智能与社会治理专题","pdfSize":"943","zuoZhe_CN":"谭新雨","risUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=Ris&id=7134","title_cn":"生成式人工智能大模型嵌入社会治理:赋能场景、风险样态与规制路径","doi":"10.11778/j.jnxb.20242259","jieShuYe":"111","keywordList_en":["large generative AI models","social governance","inter-construction theory","risk pattern","AI governance"],"endNoteUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=EndNote&id=7134","zhaiyao_en":"Large generative AI models (LGAIMs), exemplified by ChatGPT, have not only brought tremendous changes to human social life but also become deeply integrated into the modern social governance system, continuously driving the evolution of government structures and the innovation of governance models. While the original intention and essence of embedding LGAIMs into social governance is to leverage artificial intelligence (AI) technology to safeguard public interests and pursue public values, these technologies inevitably cause new risks and challenges in practice. Existing literature has explored the risk patterns and governance pathways associated with the embedding of LGAIMs in social governance, focusing on the conflict between political values and instrumental values, as well as the balance between public authority and algorithmic power. However, the interactive relationship between LGAIMs, government organizational structures, and social governance orders has not been explored in depth. Furthermore, there has not been a precise analysis of the risk patterns and regulatory pathways, considering the typical empowerment scenarios of LGAIMs.Drawing on the inter-construction theory of technology and organization, as well as technology and society, this study delves in the empowerment scenarios, risk patterns, and regulatory pathways of LGAIMs embedded into social governance. First, LGAIMs contribute to the construction of algorithmic decision-making systems in social governance, facilitating the shift from bureaucratic decision-making driven by human emotions to algorithmic rationality. However, this transformation faces challenges related to moral and responsibility judgments, necessitating a technology-for-good approach to guide the development of algorithmic decision-making models and intelligent systems in governance. Second, LGAIMs break the “information isolated island” phenomenon that often arises in traditional social governance, enabling effective cross-departmental and cross-level human-computer collaboration. Nonetheless, there is a risk of technological alienation, which makes it essential to ensure the primacy of human agency in social governance activities. Third, LGAIMs enable the scientific calculation of public service demands and accurate identification of social governance contradictions, advancing the precise matching of “supply and demand” in social governance. Nevertheless, this can also lead to the risk of social stereotyping and bias, making it essential to adhere to public value principles of fairness, justice, democracy, and equality. Fourth, LGAIMs support the construction of smart social governance scenarios characterized by virtual-physical symbiosis and human-computer interaction; however, there is a risk of undermining citizens' rights, necessitating the establishment of a multi-agent collaborative governance model focused on safeguarding civil rights. This study expands the theoretical framework in two aspects. First, this study, based on the inter-construction theory of technology and organization, as well as technology and society, profoundly reveals the operational patterns of embedding LGAIMs into social governance. In particular, this study proposes a technology-for-good approach and a collaborative governance model to balance the conflict between political values and instrumental values during the inter-construction process between technology and organization. Similarly, this study advocates for humanistic principles and public value objectives to balance the tension between public authority and algorithmic power in the inter-construction of technology and society. Second, this study highlights key social governance scenarios, examining the empowerment effects, risk patterns, and regulatory pathways arising from the integration of LGAIMs. It further advances the contextualized study of embedding LGAIMs with social governance. This study provides policy recommendations for government agencies seeking to deploy LGAIMs in decision-making, strengthen interdepartmental collaboration, analyze and address governance contradictions, and optimize service provision. These recommendations include the formulation of target value orientations, the establishment of a risk regulatory framework, the development of an ethical system, and the promotion of a collaborative governance model.","bibtexUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/article/getTxtFile.do?fileType=BibTeX&id=7134","abstractUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/10.11778/j.jnxb.20242259","zuoZheCn_L":"谭新雨","juanUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/Y2024","lanMu_en":"","qiUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/Y2024/V46/I12","zuoZhe_EN":"TAN Xinyu","risUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/article/getTxtFile.do?fileType=Ris&id=7134","title_en":"A Study on Empowerment Scenarios, Risk Patterns, and Regulatory Pathways for Integrating Large Generative AI Models into Social Governance","hasPdf":"true"},"authorNotes_cn":["谭新雨,华东理工大学社会与公共管理学院。"]};if(window.metaData && (!window.metaData.authorNotesCommon_cn && !window.metaData.authorNotesCorresp_cn && window.metaData.authorNotes_cn)){window.metaData.authorNotesCommon_cn = window.metaData.authorNotes_cn;}if(window.metaData && (!window.metaData.authorNotesCommon_en && !window.metaData.authorNotesCorresp_en && window.metaData.authorNotes_en)){window.metaData.authorNotesCommon_en = window.metaData.authorNotes_en;}var _nlmdtdXml = $("#article_nlmdtdXml").val();var magDir = _nlmdtdXml.replace(/\/[^\/]+$/,'');window.metaData.magDir = magDir;new mag_vue({ el: '#metaVue', //dataUrl: mag_currentQikanUrl() + '/EN/article/getRichHtmlJson.do?articleId='+$("#articleId").val(), data:window.metaData, loading:true, doTextFun:function(text){ return doDataJsonText(text); 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来源：2024年第12期

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