广西师范大学学报(哲学社会科学版) ›› 2025, Vol. 61 ›› Issue (2): 39-50.doi: 10.16088/j.issn.1001-6597.2025.02.004

• 治理现代化研究 • 上一篇    下一篇

智能化治理的运作机制、风险挑战与实践准则

罗昕, 张瑾杰   

  1. 暨南大学 新闻与传播学院,广东 广州 510632
  • 收稿日期:2024-05-10 出版日期:2025-03-05 发布日期:2025-02-26
  • 作者简介:罗昕(1973—),男,江西吉安人,暨南大学新闻与传播学院教授、博士生导师,研究方向:互联网治理、媒体融合、网络舆情;张瑾杰(1997—),男,福建福州人,暨南大学新闻与传播学院博士研究生,研究方向:媒体融合、互联网治理。
  • 基金资助:
    国家社会科学基金重大招标项目“媒体深度融合发展与新时代社会治理模式创新研究”(19ZDA332)

The Operation Mechanism, Risk Challenges and Practice Guidelines of Intelligentized Governance

LUO Xin, ZHANG Jin-jie   

  1. School of Journalism and Communication, Jinan University, Guangzhou 510632, China
  • Received:2024-05-10 Online:2025-03-05 Published:2025-02-26

摘要: 智能化治理是人工智能时代治理的新形态,也是媒介化治理的崭新阶段。当前公共问题的日益复杂性和治理技术的日益智能化,正在催生一种新形态的治理范式——智能化治理。基于“技术—社会”的互动视角,智能化治理的运作机制包含以下几方面:主体层面,广泛连接人类与非人类等多元行动者,编织智能生态中的共治网络;内容层面,打破资源壁垒的限制,在万物皆媒的时空中挖掘数据与信息的深层价值;方式层面,通过行政程序自动化决策,精简优化传统时期烦琐的运作流程;对象层面,以统计分析的形式预测目标行为,对特定风险进行研判与预警。智能化治理存在社会偏见与技术偏见的型构、无形之物运转难以洞察的算法黑箱以及与公共治理逻辑的冲突地带,需要通过公共性原则、敏捷性原则和数字善治原则加以应对。

关键词: 智能化治理, 自动决策, 智能预测, 算法偏见, 媒介化治理

Abstract: Intelligentized governance is a new form of governance in the era of artificial intelligence and also represents a novel phase in mediatized governance. The increasing complexity of public issues and the growing sophistication of governance technologies are giving rise to a new paradigm of governance-intelligentized governance. From an “technology-society” interactive perspective, the operational mechanism of intelligentized governance includes the following aspects: at the level of actors, it broadly connects diverse agents, both human and non-human, thus weaving a co-governance network within the intelligent ecosystem; at the content level, it breaks down resource barriers to extract the deep value of data and information in a world where everything can act as a medium; at the method level, it streamlines and optimizes the cumbersome operational processes of traditional times through automated decision-making in administrative procedures; at the object level, it predicts target behaviors through statistical analysis and conducts assessments and early warnings for specific risks. Intelligentized governance faces challenges such as the formation of social and technological biases, the opaque operation of intangible algorithms in black boxes, and conflicts with the logic of public governance. These challenges need to be addressed through principles of publicness, agility, and digital good governance.

Key words: intelligentized governance, automatic decision-making, intelligent prediction, algorithm bias, mediatized governance

中图分类号:  D63

[1] Esmark A. Maybe it is time to rediscover technocracy? An old framework for a new analysis of administrative reforms in the governance era[J]. Journal of Public Administration Research and Theory, 2017, 27(3): 501-516.
[2] 刘永谋.智能社会与技术治理[J].金融博览,2020(6):24-25.
[3] 刘永谋.智能治理的哲学反思[J].中国人民大学学报,2022(3):46-55.
[4] Alanyali M, Preis T, Moat H S. Tracking protests using geotagged flickr photographs[J]. PLOS One, 2016, 11(3): 1-8.
[5] Garcia-Herranz M, Moro E, Cebrian M, et al. Using friends as sensors to detect global-scale contagious outbreaks[J]. PLOS One, 2014, 9(4): 1-7.
[6] Moore F C, Obradovich N. Using remarkability to define coastal flooding thresholds[J]. Nature Communications, 2020, 11(1): 530.
[7] Danaher J, Hogan M J, Noone C, et al. Algorithmic governance: developing a research agenda through the power of collective intelligence[J]. Big Data & Society, 2017, 4(2): 1-21.
[8] Cugurullo F.Urban artificial intelligence: from automation to autonomy in the smart city[J].Frontiers in Sustainable Cities, 2020, 2:38.
[9] Rader E, Gray R. Understanding user beliefs about algorithmic curation in the Facebook news feed[C]//Proceedings of the 33rd annual ACM conference on human factors in computing systems. 2015: 173-182.
[10] Peeters R, Schuilenburg M. Machine justice: governing security through the bureaucracy of algorithms[J]. Information Polity, 2018, 23(3): 267-280.
[11] Ozmen Garibay O, Winslow B, Andolina S, et al. Six human-centered artificial intelligence grand challenges[J]. International Journal of Human-Computer Interaction, 2023, 39(3): 391-437.
[12] 李春雷,任慧.媒介化治理:理论逻辑、过程性建构与问题治理取向[J].苏州大学学报(哲学社会科学版),2023(6):167-174.
[13] 闫文捷,潘忠党,吴红雨.媒介化治理——电视问政个案的比较分析[J].新闻与传播研究,2020(11):37-56,126-127.
[14] 郭小安,赵海明.媒介化治理:概念辨析、价值重塑与前景展望[J].西北师大学报(社会科学版),2023(1):59-67.
[15] 姜晓萍,阿海曲洛.社会治理体系的要素构成与治理效能转化[J].理论探讨,2020(3):142-148,2.
[16] Viale Pereira G, Cunha M A, Lampoltshammer T J, et al. Increasing collaboration and participation in smart city governance: a cross-case analysis of smart city initiatives[J]. Information Technology for Development, 2017, 23(3): 526-553.
[17] Cardullo P, Kitchin R. Being a ‘citizen' in the smart city: up and down the scaffold of smart citizen participation in Dublin, Ireland[J]. GeoJournal, 2019, 84(1): 1-13.
[18] Webster C W R, Leleux C. Smart governance: opportunities for technologically-mediated citizen co-production[J]. Information Polity, 2018, 23(1): 95-110.
[19] Seaver N. Algorithms as culture: some tactics for the ethnography of algorithmic systems[J]. Big data & society, 2017, 4(2): 1-12.
[20] 吴莹,卢雨霞,陈家建,等.跟随行动者重组社会——读拉图尔的《重组社会:行动者网络理论》[J].社会学研究,2008(2):218-234.
[21] 张海柱.行动者网络理论视域下的算法黑箱与风险治理[J].科学学研究,2023(9):1545-1551.
[22] Barns S, Cosgrave E, Acuto M, et al. Digital infrastructures and urban governance[J]. Urban Policy and Research, 2017, 35(1): 20-31.
[23] Allam Z, Dhunny Z A. On big data, artificial intelligence and smart cities[J]. Cities, 2019, 89: 80-91.
[24] Malik, K. As surveillance culture grows, can we even hope to escape its reach?[DB/OL]. (2020-04-15)[2024-05-01]. https://www. theguardian.com/commentisfree/2019/may/19/as-surveillance-culture-grows-can-we-even-hope-to-escape-its-reach.
[25] Eggers W D, Skowron J. Forces of change: Smart cities[DB/OL]. (2018-03-22)[2024-05-01].https://www2.deloitte.com/us/en/insights/focus/smart-city/overview.html.
[26] Guo K, Lu Y, Gao H, et al. Artificial intelligence-based semantic internet of things in a user-centric smart city[J]. Sensors, 2018, 18(5): 1341.
[27] Bovens M, Zouridis S. From street-level to system-level bureaucracies: how information and communication technology is transforming administrative discretion and constitutional control[J]. Public Administration Review, 2002, 62(2): 174-184.
[28] Van der Voort H G, Klievink A J, Arnaboldi M, et al. Rationality and politics of algorithms. Will the promise of big data survive the dynamics of public decision making?[J]. Government Information Quarterly, 2019, 36(1): 27-38.
[29] 李晓方,王友奎,孟庆国.政务服务智能化:典型场景、价值质询和治理回应[J].电子政务,2020(2):2-10.
[30] Abduljabbar R, Dia H, Liyanage S, et al. Applications of artificial intelligence in transport: an overview[J]. Sustainability, 2019, 11(1): 189.
[31] Gorwa R, Binns R, Katzenbach C. Algorithmic content moderation: technical and political challenges in the automation of platform governance[J]. Big Data & Society, 2020, 7(1): 1-15.
[32] Danaher J, Hogan M J, Noone C, et al. Algorithmic governance: developing a research agenda through the power of collective intelligence[J]. Big Data & Society, 2017, 4(2): 1-21.
[33] Lansing S. New York State COMPAS-probation risk and need assessment study: examining the recidivism scale's effectiveness and predictive accuracy[R]. New YorkState: Division of Criminal Justice Services, 2012.
[34] Coglianese C. Algorithmic regulation: machine learning as a governance tool[C]//Schuilenburg M, Peeters R. The Algorithmic Society. London: Routledge, 2020: 35-52.
[35] Hjarvard S. The mediatization of society[J]. Nordicom Review, 2008, 29(2): 102-131.
[36] Hepp A. Cultures of mediatization[M].Cambridge:Polity Press, 2013: 618.
[37] 戴宇辰.媒介化研究的“中间道路”:物质性路径与传播型构[J].南京社会科学,2021(7):104-112,121.
[38] Angwin J, Larson J, Mattu S, et al. Machine bias[C]//Martin K. Ethics of data and analytics. New York: Auerbach Publications, 2022: 254-264.
[39] Coen R, Paul E, Vanegas P, et al. A user-centered perspective on algorithmic personalization[EB/OL]. University of California, Berkeley MIMS Final Project. https://www. ischool. berkeley. edu/projects/2016/user-centeredperspective-algorithmic-personalization, 2016.
[40] Benjamin R. Assessing risk, automating racism[J]. Science, 2019, 366(6464): 421-422.
[41] 吴小坤,邓可晴.算法偏见背后的数据选择、信息过滤与协同治理[J].中国出版,2024(6):10-15.
[42] Blier N. Bias in AI and machine learning: Sources and solutions[EB/OL]. (2022-11-09)[2024-05-01]. https://www.lexalytics.com/blog/bias-in-ai-machine-learning/.
[43] Mitchell M, Baker D, Moorosi N, et al. Diversity and inclusion metrics in subset selection[C]//Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society. 2020: 117-123.
[44] Došilović F K, Brčić M, Hlupić N. Explainable artificial intelligence: a survey[C]//2018 41st international convention on information and communication technology, electronics and microelectronics (MIPRO). IEEE, 2018: 0210-0215.
[45] Rai A. Explainable AI: from black box to glass box[J]. Journal of the Academy of Marketing Science, 2020, 48:137-141.
[46] 张欣.生成式人工智能的算法治理挑战与治理型监管[J].现代法学,2023,45(3):108-123.
[47] Chander A. The racist algorithm[J]. Mich. L. Rev., 2016, 115: 1023.
[48] Citron D K, Pasquale F. The scored society: due process for automated predictions[J]. Washington Law Review, 2014, 89: 1.
[49] Pasquale F. Restoring transparency to automated authority[J].Journal on Telecommunications and High Technology Law, 2011, 9: 235-252.
[50] Zambonelli F, Salim F, Loke S W, et al. Algorithmic governance in smart cities: the conundrum and the potential of pervasive computing solutions[J]. IEEE Technology and Society Magazine, 2018, 37(2): 80-87.
[51] Arrieta A B, Díaz-Rodríguez N, Del Ser J, et al. Explainable Artificial Intelligence (XAI): concepts, taxonomies, opportunities and challenges toward responsible AI[J]. Information Fusion, 2020, 58: 82-115.
[52] Ryan S. Google Clamps Down on Content Factories[EB/OL]. (2011-02-25)[2024-05-01].https://www.wired.com/2011/02/google-clamp-down-content-factories/.
[53] Stohl C, Stohl M, Leonardi P M. Managing opacity: information visibility and the paradox of transparency in the digital age[J]. International Journal of Communication, 2016, 10:123-137.
[54] 罗昕.媒介化治理:在媒介逻辑与治理逻辑之间[J].湖南师范大学社会科学学报,2022(5):1-11.
[55] Allam Z, Newman P. Economically incentivising smart urban regeneration. Case study of Port Louis, Mauritius[J]. Smart Cities, 2018, 1(1): 53-74.
[56] Montjoye Y A, Farzanehfar A, Hendrickx J, et al. Solving artificial intelligence's privacy problem[J]. Field Actions Science Reports. The Journal of Field Actions, 2017 (Special Issue 17): 80-83.
[57] Bonnefon J F, Shariff A, Rahwan I. The social dilemma of autonomous vehicles[J]. Science, 2016, 352(6293): 1573-1576.
[58] Danks D , London A J.Algorithmic bias in autonomous systems[C]//Proceedings of the 26th International Joint Conference on Artificial Intelligence, 2017:4691-4697.
[59] Bucher T. Neither black nor box: ways of knowing algorithms[C]//Kubitschko S, Kaun A. Innovative methods in media and communication research. Cham: Springer International Publishing, 2016:81-98.
[60] Loi M, Ferrario A, Viganò E. Transparency as design publicity: explaining and justifying inscrutable algorithms[J]. Ethics and Information Technology, 2021, 23(3): 253-263.
[61] Mergel I, Ganapati S, Whitford A B. Agile: a new way of governing[J]. Public Administration Review, 2021, 81(1): 161-165.
[62] Mergel I, Gong Y, Bertot J. Agile government: systematic literature review and future research[J]. Government Information Quarterly, 2018, 35(2): 291-298.
[63] 韩兆柱,申帅杰.敏捷治理:人工智能治理新模式[J].华东理工大学学报(社会科学版),2024(1):105-119,132.
[64] 于文轩,魏炜.数据的敏捷治理:价值重塑与框架构建[J].广西师范大学学报(哲学社会科学版),2022(5):37-49.
[65] Mashaw J L. Reasoned administration: the European Union, the United States, and the project of democratic governance[M]//The George Washington Law Review, 2007,76(1): 99-124.
[66] Widlak A, van Eck M, Peeters R. Towards principles of good digital administration: fairness, accountability and proportionality in automated decision-making[C]//Schuilnburg M, Peeters R. The Algorithmic Society. London: Routledge, 2020: 67-83.
[1] 李春雷, 李娟. 网络公共事件的媒介化治理实践进路——基于公众记忆周期的视角[J]. 广西师范大学学报(哲学社会科学版), 2025, 61(2): 29-38.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] 张一兵. 从绝对到抽象:空间的历史——列菲伏尔《空间的生产》解读[J]. 广西师范大学学报(哲学社会科学版), 2025, 61(2): 1 -19 .
[2] 赵小宇, 韩秋红. 新质生产力的历史唯物主义意涵[J]. 广西师范大学学报(哲学社会科学版), 2025, 61(2): 20 -28 .
[3] 李春雷, 李娟. 网络公共事件的媒介化治理实践进路——基于公众记忆周期的视角[J]. 广西师范大学学报(哲学社会科学版), 2025, 61(2): 29 -38 .
[4] 孙杰远, 杨小微, 徐冬青, 程亮, 游韵. 教育现代化的“中国式”笔谈[J]. 广西师范大学学报(哲学社会科学版), 2025, 61(2): 51 -64 .
[5] 张智, 高书国. 教育强国的理论创新与系统提升——学习领会习近平总书记在全国教育大会上的重要讲话精神[J]. 广西师范大学学报(哲学社会科学版), 2025, 61(2): 65 -74 .
[6] 杨丽萍, 刘溢云. 文化哲学视域下中国教育家精神的意蕴要旨与养成之道[J]. 广西师范大学学报(哲学社会科学版), 2025, 61(2): 75 -86 .
[7] 姚树洁, 张小倩. 新质生产力推进区域协调发展的理论及实践路径[J]. 广西师范大学学报(哲学社会科学版), 2025, 61(2): 87 -102 .
[8] 杜运苏, 周玉润. 本土市场规模、虹吸效应与全球价值链攀升——基于跨国面板数据[J]. 广西师范大学学报(哲学社会科学版), 2025, 61(2): 103 -120 .
[9] 张林, 王龙基, 王燕霞. 数字金融使用何以影响农户创业——来自中西部地区1 525户农户的微观证据[J]. 广西师范大学学报(哲学社会科学版), 2025, 61(2): 121 -143 .
[10] 李斌, 文彩婷. 数字技术下的艺术史书写:数字艺术史的创新与挑战[J]. 广西师范大学学报(哲学社会科学版), 2025, 61(2): 144 -155 .
版权所有 © 广西师范大学学报(哲学社会科学版)编辑部
地址:广西桂林市三里店育才路15号 邮编:541004
电话:0773-5857325 E-mail: xbgj@mailbox.gxnu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发